ZZZ (Advisor: Dr. A.A. Rodriguez, Electrical Engineering)
|
|
- Clement Eaton
- 6 years ago
- Views:
Transcription
1 Using a Fleet of Low-Cost Ground Robotic Vehicles to Play Complex Games: Development of an Artificial Intelligence (AI) Vehicle Fleet Coordination Engine GOALS. The proposed research shall focus on developing an artificial intelligence (AI) engine for a fleet of low-cost multi-capability ground robotic vehicles. More specifically, the main goal of the project is to develop, test and demonstrate an AI software gaming engine that permits vehicles to play simple and complex games; e.g. Tic-Tac-Toe [1], Connect 4 [2], a Chess-like game which involves 5 main pieces and two pawns (7 robots on each side) [3]-[6], and a more complicated GO-like game which requires surrounding an opponent s forces (again 7 robots on each side) [7]-[8]. MOTIVATION. The above is a very worthwhile activity because it combines precision control of mobile ground robots with complex algorithms [9]-[12]. It is complex algorithms when combined with sensors and actuation devices for real-time decision making which results in intelligent systems. Collectively, the two will represent a powerful test bed for the deployment and visualization of complex algorithms. Such an AI-enhanced multi-vehicle fleet can be used in each of the following important applications: (1) performance or objective-based coordination of multiple vehicles, (2) coordination of military robots/forces, (3) coordination of first responder robots/resources/agents, and (4) using the AIenhanced fleet to entertain prospective elementary school, middle school, high school and community college students that are thinking about engineering as a career; i.e. the fleet would be a great outreach tool. Broader Impact. Dr. Rodriguez plans on using the AI-enhanced fleet as engineering recruitment tool as he pursues his Academic Success and Professional Development (ASAP) Project-Based Engineering Academy Across Arizona campaign a venture involving over 15 community colleges across the state (as well as their local high schools). OBJECTIVES. The paramount objective of the proposed work is to develop several look-ahead performance-based algorithms that can be used to play the games mentioned above; i.e. Tic-Tac-Toe [1], Connect 4 [2], a Chess-like game [3]-[6], and a more complicated GO-like game [7]-[8]. CRITICAL QUESTIONS. Critical questions to be addressed in this work are as follows: (1) Look-Ahead Algorithms. What look-ahead algorithms should be implemented [9]-[12]? We do not want to consider more than 2-3 algorithms. 2-3 algorithms will be enough to systematically compare the performance of each. (2) Opponent Fleet Look-Ahead Capability. How does the performance of the algorithms depend on the look-ahead capability level of the opponent fleet? As the look-ahead capability of the opponent fleet improves, we expect algorithm performance to degrade. This shall be quantified by conducting specific empirical (simulation) studies. (3) Time-To-Solution. How does the time to compute a solution (move) depend on the look-ahead aggressiveness (i.e. the number of moves that we look ahead)? We expect the algorithms to be
2 non-polynomial time algorithms. That is, the time to compute a solution grows exponentially (non-polynomial) as the number of possible moves grows. (4) Algorithms that Improve Over Time. How do we get the algorithms to improve over time [6]; i.e. get better as they are exercised and acquire new knowledge? Many methods for doing this have been examined in the literature. We shall explore a few. (5) Robot Spatial Command Following. How do we issue spatial commands to the robots in the fleet? The answer here is provided within the following very detailed (377 page) MS thesis that Dr. Rodriguez supervised [13]. A simple vision-based Cartesian stabilization control system will do the job [14]. Establishing a Foundation for Future Work. In this work, it is the algorithms that represent the critical catalyst for the effort. While the control is essential so that the robots can move to their solutioncomputed destinations on the playing plane, it has been figured out and well documented within the aforementioned MS thesis [13]. Given this, it is natural to ask: Why bother with the controls portion of this project? The answer here is twofold. First, watching robots play chess will be exciting for many. Secondly, and more fundamentally, we view the proposed research as representing a starting point for the development of much more sophisticated fleet coordination. This could involve more complex games; e.g. soccer, basketball. At some point, we will advance to total warfare between fleets (physical and cyber). Given this, the potential impact of the proposed project can be very significant particularly when one factors the Arizona-wide impact that Dr. Rodriguez Engineering Academy efforts will have on students across Arizona; particularly low-income students, woman and underrepresented minorities. Final Demonstration. The final demonstration will involve robots playing Tic-Tac-Toe [1], Connect 4 [2], 7 piece Chess [3]-[6] and Go [7]-[8]. All results will be documented in a final comprehensive report and video. The report shall be used as the basis for submitting our work for publication in a refereed journal; e.g. IEEE Transactions on Control Applications.
3 References [1] J. Grim, P. Somol and P. Pudil, Probabilistic neural network playing and learning Tic-Tac-Toe, Pattern Recognition Letters, vol. 26, no. 12, pp , [2] A. Verma, Genetic evolution of connect four strategies, ProQuest Dissertations and Theses, pp. 198, [3] C. Ewerhart, Backward Induction and the Game-Theoretic Analysis of Chess, Games and Economic Behavior, vol. 39, no. 2, pp , [4] S. Bushinksky. Deus ex machina-a higher creative species in the game of chess. AI Magazine 30(3), pp [5] T. Shunhua and C. Miao, Search Algorithm in Five-Piece Chesss, Journal of Computing, vol. 3, no. 4, pp , [6] D. Fogel, T. Hays, S. Hahn and J. Quon, A self-learning evolutionary chess program, Proceedings of the IEEE, vol. 92, no. 12, pp , [7] K. Chen, Maximizing the chance of winning in searching Go game trees, Information Sciences, vol. 175, no. 4, pp , [8] J. Hoock, C. Lee, A. Rimmel, F. Teytaud, M. Wang and O. Teytaud, Intelligent Agents for the Game of Go, IEEE Comput. Intell. Mag., [9] K. Hausken and G. Levitin, Minmax defense strategy for complex multi-state systems, Reliability Engineering & System Safety, vol. 94, no. 2, pp , [10] F. Facchinei, J. Pang and G. Scutari, Non-cooperative games with minmax objectives, Computational Optimization and Applications, vol. 59, no. 1-2, pp , [11] K. Chellapilla and D. Fogel, Evolution, neural networks, games, and intelligence, Proceedings of the IEEE, vol. 87, no. 9, pp , [12] J. Mandziuk, Towards Cognitively Plausible Game Playing Systems, IEEE Comput. Intell. Mag., vol. 6, no. 2, pp , [13] Z. Lin, Modeling, Design and Control of Multiple Low-Cost Robotic Ground Vehicles, ASU MS Thesis, Electrical Engineering, (Supervisor: Dr. A.A. Rodriguez), 377 pages, August, [14] F. C. Vieira, A. A. D. Medeiros, P. J. Alsina, A.P. Araujo, Position and Orientation Control of a Two-Wheeled Differentially Driven Nonholonomic Mobile Robot, ICINCO Proceedings, 7 pages, 2004.
4 TIMELINE FOR Using a Fleet of Low-Cost Ground Robotic Vehicles to Play Complex Games: Development of an Artificial Intelligence (AI) Vehicle Fleet Coordination Engine Semester: Spring ZZZ Comprehensive Literature Survey October 2015-Jan 2016 Build 2 Robots January 2016 Tic-Tac-Toe and Connect 4 January- February 2016 Chess February-March 2016 GO March-April 2016 Data Collection, Add Learning Capability April 2016 Final Data Collection, Demonstration, Final Report April-May 2016
5 BUDGET FOR Using a Fleet of Low-Cost Ground Robotic Vehicles to Play Complex Games: Development of an Artificial Intelligence (AI) Vehicle Fleet Coordination Engine Semester: Spring ZZZ 2 Enhanced Thunder Tumbler Robotic Vehicles $ Books, Supplies $84.68 TOTAL: $400 Cost Breakdown for Enhanced Thunder Tumbler Robot Product/Component Quantity Price ($) $ Thunder Tumbler Vehicle 1 $10 $ Raspberry Pi 2 Model B 1 $40 $ Arduino Uno 1 $ $12.19 Adafruit Motor Shield 1 $ $22.50 Raspberry Pi 5MP Camera 1 $25 $ Camera Holder 1 $ $5 HCSR04 Ultrasonic Sensor 1 $ $1.87 Power Supply for Raspberry Pi 1 $10 $ Power Supply for Arduino 4 $ $6.75 Magnetic Wheel Encoders 2 $ $4.40 Adafruit 9dof IMU 1 $ $19.95 Total Price $ $ Two Enhanced Thunder Tumblers will be built so that we can progress toward a fleet size of approximately 16 vehicles.
Secure High-Bandwidth Communications for a Fleet of Low-Cost Ground Robotic Vehicles. ZZZ (Advisor: Dr. A.A. Rodriguez, Electrical Engineering)
Secure High-Bandwidth Communications for a Fleet of Low-Cost Ground Robotic Vehicles GOALS. The proposed research shall focus on meeting critical objectives toward achieving the long-term goal of developing
More informationGround Robot with an Arm to Perform Simple Grasp and Place Tasks Juan Ortiz, ASU, Computer Systems Engineering
Ground Robot with an Arm to Perform Simple Grasp and Place Tasks Juan Ortiz, ASU, Computer Systems Engineering GOAL: The goal of the proposed research on simple grasp and place tasks using a ground robot
More informationThis list supersedes the one published in the November 2002 issue of CR.
PERIODICALS RECEIVED This is the current list of periodicals received for review in Reviews. International standard serial numbers (ISSNs) are provided to facilitate obtaining copies of articles or subscriptions.
More informationDevelopment and Integration of Artificial Intelligence Technologies for Innovation Acceleration
Development and Integration of Artificial Intelligence Technologies for Innovation Acceleration Research Supervisor: Minoru Etoh (Professor, Open and Transdisciplinary Research Initiatives, Osaka University)
More informationCS 4700: Foundations of Artificial Intelligence
CS 4700: Foundations of Artificial Intelligence Bart Selman Reinforcement Learning R&N Chapter 21 Note: in the next two parts of RL, some of the figure/section numbers refer to an earlier edition of R&N
More informationWireless Powered Chess: - A Review
Wireless Powered Chess: - A Review Prof.R.D.Sushir 1, Manish A.Chhangani 2 1 Prof. Dept. of Electronics and telecommunication, P.R. Patil College of engineering, Amravati, India 2 Student of M.E Department
More informationUNIVERSIDAD CARLOS III DE MADRID ESCUELA POLITÉCNICA SUPERIOR
UNIVERSIDAD CARLOS III DE MADRID ESCUELA POLITÉCNICA SUPERIOR TRABAJO DE FIN DE GRADO GRADO EN INGENIERÍA DE SISTEMAS DE COMUNICACIONES CONTROL CENTRALIZADO DE FLOTAS DE ROBOTS CENTRALIZED CONTROL FOR
More informationThe Future of AI A Robotics Perspective
The Future of AI A Robotics Perspective Wolfram Burgard Autonomous Intelligent Systems Department of Computer Science University of Freiburg Germany The Future of AI My Robotics Perspective Wolfram Burgard
More informationComputer Vision Navigation for Robotic Campus Guide
FURI Proposal for Fall 2018 Education, Sustainability Computer Vision Navigation for Robotic Campus Guide Zakk Giacometti, Computer Systems Engineering Advisor: Dr. Armando A. Rodriguez, Professor of Electrical
More informationSession 11 Introduction to Robotics and Programming mbot. >_ {Code4Loop}; Roochir Purani
Session 11 Introduction to Robotics and Programming mbot >_ {Code4Loop}; Roochir Purani RECAP from last 2 sessions 3D Programming with Events and Messages Homework Review /Questions Understanding 3D Programming
More informationDr. Wenjie Dong. The University of Texas Rio Grande Valley Department of Electrical Engineering (956)
Dr. Wenjie Dong The University of Texas Rio Grande Valley Department of Electrical Engineering (956) 665-2200 Email: wenjie.dong@utrgv.edu EDUCATION PhD, University of California, Riverside, 2009 Major:
More informationCOS 402 Machine Learning and Artificial Intelligence Fall Lecture 1: Intro
COS 402 Machine Learning and Artificial Intelligence Fall 2016 Lecture 1: Intro Sanjeev Arora Elad Hazan Today s Agenda Defining intelligence and AI state-of-the-art, goals Course outline AI by introspection
More informationMinimax Trees: Utility Evaluation, Tree Evaluation, Pruning
Minimax Trees: Utility Evaluation, Tree Evaluation, Pruning CSCE 315 Programming Studio Fall 2017 Project 2, Lecture 2 Adapted from slides of Yoonsuck Choe, John Keyser Two-Person Perfect Information Deterministic
More informationNAVIGATION OF MOBILE ROBOT USING THE PSO PARTICLE SWARM OPTIMIZATION
Journal of Academic and Applied Studies (JAAS) Vol. 2(1) Jan 2012, pp. 32-38 Available online @ www.academians.org ISSN1925-931X NAVIGATION OF MOBILE ROBOT USING THE PSO PARTICLE SWARM OPTIMIZATION Sedigheh
More informationThe first topic I would like to explore is probabilistic reasoning with Bayesian
Michael Terry 16.412J/6.834J 2/16/05 Problem Set 1 A. Topics of Fascination The first topic I would like to explore is probabilistic reasoning with Bayesian nets. I see that reasoning under situations
More informationCS 1571 Introduction to AI Lecture 12. Adversarial search. CS 1571 Intro to AI. Announcements
CS 171 Introduction to AI Lecture 1 Adversarial search Milos Hauskrecht milos@cs.pitt.edu 39 Sennott Square Announcements Homework assignment is out Programming and experiments Simulated annealing + Genetic
More informationGames (adversarial search problems)
Mustafa Jarrar: Lecture Notes on Games, Birzeit University, Palestine Fall Semester, 204 Artificial Intelligence Chapter 6 Games (adversarial search problems) Dr. Mustafa Jarrar Sina Institute, University
More informationUNIT 13A AI: Games & Search Strategies
UNIT 13A AI: Games & Search Strategies 1 Artificial Intelligence Branch of computer science that studies the use of computers to perform computational processes normally associated with human intellect
More informationReactive Planning with Evolutionary Computation
Reactive Planning with Evolutionary Computation Chaiwat Jassadapakorn and Prabhas Chongstitvatana Intelligent System Laboratory, Department of Computer Engineering Chulalongkorn University, Bangkok 10330,
More informationCS 2710 Foundations of AI. Lecture 9. Adversarial search. CS 2710 Foundations of AI. Game search
CS 2710 Foundations of AI Lecture 9 Adversarial search Milos Hauskrecht milos@cs.pitt.edu 5329 Sennott Square CS 2710 Foundations of AI Game search Game-playing programs developed by AI researchers since
More informationCPS331 Lecture: Agents and Robots last revised November 18, 2016
CPS331 Lecture: Agents and Robots last revised November 18, 2016 Objectives: 1. To introduce the basic notion of an agent 2. To discuss various types of agents 3. To introduce the subsumption architecture
More informationCPS331 Lecture: Search in Games last revised 2/16/10
CPS331 Lecture: Search in Games last revised 2/16/10 Objectives: 1. To introduce mini-max search 2. To introduce the use of static evaluation functions 3. To introduce alpha-beta pruning Materials: 1.
More informationRoboCup. Presented by Shane Murphy April 24, 2003
RoboCup Presented by Shane Murphy April 24, 2003 RoboCup: : Today and Tomorrow What we have learned Authors Minoru Asada (Osaka University, Japan), Hiroaki Kitano (Sony CS Labs, Japan), Itsuki Noda (Electrotechnical(
More informationCPS331 Lecture: Agents and Robots last revised April 27, 2012
CPS331 Lecture: Agents and Robots last revised April 27, 2012 Objectives: 1. To introduce the basic notion of an agent 2. To discuss various types of agents 3. To introduce the subsumption architecture
More informationA Brief Introduction to Game Theory
A Brief Introduction to Game Theory Jesse Crawford Department of Mathematics Tarleton State University November 20, 2014 (Tarleton State University) Brief Intro to Game Theory November 20, 2014 1 / 36
More informationMRS: an Autonomous and Remote-Controlled Robotics Platform for STEM Education
Association for Information Systems AIS Electronic Library (AISeL) SAIS 2015 Proceedings Southern (SAIS) 2015 MRS: an Autonomous and Remote-Controlled Robotics Platform for STEM Education Timothy Locke
More informationSynthetic Brains: Update
Synthetic Brains: Update Bryan Adams Computer Science and Artificial Intelligence Laboratory (CSAIL) Massachusetts Institute of Technology Project Review January 04 through April 04 Project Status Current
More informationFACULTY MENTOR Khoshabeh, Ramsin. PROJECT TITLE PiB: Learning Python
PiB: Learning Python hands-on development skills to engineering students. This PiB is a set of independent programs that strengthen the student s programming skills through Python, utilizing Python libraries
More informationAdversary Search. Ref: Chapter 5
Adversary Search Ref: Chapter 5 1 Games & A.I. Easy to measure success Easy to represent states Small number of operators Comparison against humans is possible. Many games can be modeled very easily, although
More informationGame Playing. Garry Kasparov and Deep Blue. 1997, GM Gabriel Schwartzman's Chess Camera, courtesy IBM.
Game Playing Garry Kasparov and Deep Blue. 1997, GM Gabriel Schwartzman's Chess Camera, courtesy IBM. Game Playing In most tree search scenarios, we have assumed the situation is not going to change whilst
More informationInternational Research Master Level 2 - Master 3EA «Electronics, Electrical Energy, Automatics»
International Research Master Level 2 - Master 3EA «Electronics, Electrical Energy, Automatics» Centre Val de Loire Region France LOCALISATION AREA PARIS Education part: Two institutions involved Research
More informationARTIFICIAL INTELLIGENCE (CS 370D)
Princess Nora University Faculty of Computer & Information Systems ARTIFICIAL INTELLIGENCE (CS 370D) (CHAPTER-5) ADVERSARIAL SEARCH ADVERSARIAL SEARCH Optimal decisions Min algorithm α-β pruning Imperfect,
More informationUSING A FUZZY LOGIC CONTROL SYSTEM FOR AN XPILOT COMBAT AGENT ANDREW HUBLEY AND GARY PARKER
World Automation Congress 21 TSI Press. USING A FUZZY LOGIC CONTROL SYSTEM FOR AN XPILOT COMBAT AGENT ANDREW HUBLEY AND GARY PARKER Department of Computer Science Connecticut College New London, CT {ahubley,
More informationThe Co-Evolvability of Games in Coevolutionary Genetic Algorithms
The Co-Evolvability of Games in Coevolutionary Genetic Algorithms Wei-Kai Lin Tian-Li Yu TEIL Technical Report No. 2009002 January, 2009 Taiwan Evolutionary Intelligence Laboratory (TEIL) Department of
More informationArtificial Intelligence: Implications for Autonomous Weapons. Stuart Russell University of California, Berkeley
Artificial Intelligence: Implications for Autonomous Weapons Stuart Russell University of California, Berkeley Outline AI and autonomy State of the art Likely future developments Conclusions What is AI?
More informationArtificial Intelligence. Minimax and alpha-beta pruning
Artificial Intelligence Minimax and alpha-beta pruning In which we examine the problems that arise when we try to plan ahead to get the best result in a world that includes a hostile agent (other agent
More informationUnit 12: Artificial Intelligence CS 101, Fall 2018
Unit 12: Artificial Intelligence CS 101, Fall 2018 Learning Objectives After completing this unit, you should be able to: Explain the difference between procedural and declarative knowledge. Describe the
More informationEvolving High-Dimensional, Adaptive Camera-Based Speed Sensors
In: M.H. Hamza (ed.), Proceedings of the 21st IASTED Conference on Applied Informatics, pp. 1278-128. Held February, 1-1, 2, Insbruck, Austria Evolving High-Dimensional, Adaptive Camera-Based Speed Sensors
More informationRobotics Education in Emerging Technology Regions
Robotics Education in Emerging Technology Regions G. Ayorkor Mills-Tettey Robotics Institute, Carnegie Mellon University M. Bernardine Dias, Brett Browning (Carnegie Mellon University) Nathan Amanquah
More informationKeywords: Multi-robot adversarial environments, real-time autonomous robots
ROBOT SOCCER: A MULTI-ROBOT CHALLENGE EXTENDED ABSTRACT Manuela M. Veloso School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213, USA veloso@cs.cmu.edu Abstract Robot soccer opened
More informationA Brief Introduction to Game Theory
A Brief Introduction to Game Theory Jesse Crawford Department of Mathematics Tarleton State University April 27, 2011 (Tarleton State University) Brief Intro to Game Theory April 27, 2011 1 / 35 Outline
More informationHierarchical Controller for Robotic Soccer
Hierarchical Controller for Robotic Soccer Byron Knoll Cognitive Systems 402 April 13, 2008 ABSTRACT RoboCup is an initiative aimed at advancing Artificial Intelligence (AI) and robotics research. This
More informationImplicit Fitness Functions for Evolving a Drawing Robot
Implicit Fitness Functions for Evolving a Drawing Robot Jon Bird, Phil Husbands, Martin Perris, Bill Bigge and Paul Brown Centre for Computational Neuroscience and Robotics University of Sussex, Brighton,
More informationSolving Problems by Searching: Adversarial Search
Course 440 : Introduction To rtificial Intelligence Lecture 5 Solving Problems by Searching: dversarial Search bdeslam Boularias Friday, October 7, 2016 1 / 24 Outline We examine the problems that arise
More informationAN AUTONOMOUS SIMULATION BASED SYSTEM FOR ROBOTIC SERVICES IN PARTIALLY KNOWN ENVIRONMENTS
AN AUTONOMOUS SIMULATION BASED SYSTEM FOR ROBOTIC SERVICES IN PARTIALLY KNOWN ENVIRONMENTS Eva Cipi, PhD in Computer Engineering University of Vlora, Albania Abstract This paper is focused on presenting
More informationOutline. What is AI? A brief history of AI State of the art
Introduction to AI Outline What is AI? A brief history of AI State of the art What is AI? AI is a branch of CS with connections to psychology, linguistics, economics, Goal make artificial systems solve
More informationBehaviour-Based Control. IAR Lecture 5 Barbara Webb
Behaviour-Based Control IAR Lecture 5 Barbara Webb Traditional sense-plan-act approach suggests a vertical (serial) task decomposition Sensors Actuators perception modelling planning task execution motor
More informationUsing a genetic algorithm for mining patterns from Endgame Databases
0 African Conference for Sofware Engineering and Applied Computing Using a genetic algorithm for mining patterns from Endgame Databases Heriniaina Andry RABOANARY Department of Computer Science Institut
More informationCS295-1 Final Project : AIBO
CS295-1 Final Project : AIBO Mert Akdere, Ethan F. Leland December 20, 2005 Abstract This document is the final report for our CS295-1 Sensor Data Management Course Final Project: Project AIBO. The main
More informationTransactions on Information and Communications Technologies vol 6, 1994 WIT Press, ISSN
Application of artificial neural networks to the robot path planning problem P. Martin & A.P. del Pobil Department of Computer Science, Jaume I University, Campus de Penyeta Roja, 207 Castellon, Spain
More informationMotion Control of a Three Active Wheeled Mobile Robot and Collision-Free Human Following Navigation in Outdoor Environment
Proceedings of the International MultiConference of Engineers and Computer Scientists 2016 Vol I,, March 16-18, 2016, Hong Kong Motion Control of a Three Active Wheeled Mobile Robot and Collision-Free
More informationImplementation of a Self-Driven Robot for Remote Surveillance
International Journal of Research Studies in Science, Engineering and Technology Volume 2, Issue 11, November 2015, PP 35-39 ISSN 2349-4751 (Print) & ISSN 2349-476X (Online) Implementation of a Self-Driven
More informationBehaviour Patterns Evolution on Individual and Group Level. Stanislav Slušný, Roman Neruda, Petra Vidnerová. CIMMACS 07, December 14, Tenerife
Behaviour Patterns Evolution on Individual and Group Level Stanislav Slušný, Roman Neruda, Petra Vidnerová Department of Theoretical Computer Science Institute of Computer Science Academy of Science of
More informationA.I in Automotive? Why and When.
A.I in Automotive? Why and When. AGENDA 01 02 03 04 Definitions A.I? A.I in automotive Now? Next big A.I breakthrough in Automotive 01 DEFINITIONS DEFINITIONS Artificial Intelligence Artificial Intelligence:
More informationMonte Carlo Tree Search
Monte Carlo Tree Search 1 By the end, you will know Why we use Monte Carlo Search Trees The pros and cons of MCTS How it is applied to Super Mario Brothers and Alpha Go 2 Outline I. Pre-MCTS Algorithms
More informationOPEN SOURCES-BASED COURSE «ROBOTICS» FOR INCLUSIVE SCHOOLS IN BELARUS
УДК 376-056(476) OPEN SOURCES-BASED COURSE «ROBOTICS» FOR INCLUSIVE SCHOOLS IN BELARUS Nikolai Gorbatchev, Iouri Zagoumennov Belarus Educational Research Assosiation «Innovations in Education», Belarus
More information* Intelli Robotic Wheel Chair for Specialty Operations & Physically Challenged
ADVANCED ROBOTICS SOLUTIONS * Intelli Mobile Robot for Multi Specialty Operations * Advanced Robotic Pick and Place Arm and Hand System * Automatic Color Sensing Robot using PC * AI Based Image Capturing
More informationCPS331 Lecture: Intelligent Agents last revised July 25, 2018
CPS331 Lecture: Intelligent Agents last revised July 25, 2018 Objectives: 1. To introduce the basic notion of an agent 2. To discuss various types of agents Materials: 1. Projectable of Russell and Norvig
More informationGame-playing AIs: Games and Adversarial Search I AIMA
Game-playing AIs: Games and Adversarial Search I AIMA 5.1-5.2 Games: Outline of Unit Part I: Games as Search Motivation Game-playing AI successes Game Trees Evaluation Functions Part II: Adversarial Search
More informationGame Playing State-of-the-Art CSE 473: Artificial Intelligence Fall Deterministic Games. Zero-Sum Games 10/13/17. Adversarial Search
CSE 473: Artificial Intelligence Fall 2017 Adversarial Search Mini, pruning, Expecti Dieter Fox Based on slides adapted Luke Zettlemoyer, Dan Klein, Pieter Abbeel, Dan Weld, Stuart Russell or Andrew Moore
More informationCooperative Behavior Acquisition in A Multiple Mobile Robot Environment by Co-evolution
Cooperative Behavior Acquisition in A Multiple Mobile Robot Environment by Co-evolution Eiji Uchibe, Masateru Nakamura, Minoru Asada Dept. of Adaptive Machine Systems, Graduate School of Eng., Osaka University,
More information2 Our Hardware Architecture
RoboCup-99 Team Descriptions Middle Robots League, Team NAIST, pages 170 174 http: /www.ep.liu.se/ea/cis/1999/006/27/ 170 Team Description of the RoboCup-NAIST NAIST Takayuki Nakamura, Kazunori Terada,
More informationARTIFICIAL INTELLIGENCE - ROBOTICS
ARTIFICIAL INTELLIGENCE - ROBOTICS http://www.tutorialspoint.com/artificial_intelligence/artificial_intelligence_robotics.htm Copyright tutorialspoint.com Robotics is a domain in artificial intelligence
More informationProfessor, Graduate Institute of Electro-Optical Engineering ( ~) Chairman, Institute of Engineering Science and Technology ( ~)
Rong-Fong Fung Professor, Department of Mechanical & Automation Engineering (2004-08~) Professor, Graduate Institute of Electro-Optical Engineering (2004-08~) Dean, College of Engineering (2010-08~) Chairman,
More informationCognitive Robotics 2017/2018
Cognitive Robotics 2017/2018 Course Introduction Matteo Matteucci matteo.matteucci@polimi.it Artificial Intelligence and Robotics Lab - Politecnico di Milano About me and my lectures Lectures given by
More informationEvolutionary Computation for Creativity and Intelligence. By Darwin Johnson, Alice Quintanilla, and Isabel Tweraser
Evolutionary Computation for Creativity and Intelligence By Darwin Johnson, Alice Quintanilla, and Isabel Tweraser Introduction to NEAT Stands for NeuroEvolution of Augmenting Topologies (NEAT) Evolves
More informationMAKER: Development of Smart Mobile Robot System to Help Middle School Students Learn about Robot Perception
Paper ID #14537 MAKER: Development of Smart Mobile Robot System to Help Middle School Students Learn about Robot Perception Dr. Sheng-Jen Tony Hsieh, Texas A&M University Dr. Sheng-Jen ( Tony ) Hsieh is
More informationModule 3. Problem Solving using Search- (Two agent) Version 2 CSE IIT, Kharagpur
Module 3 Problem Solving using Search- (Two agent) 3.1 Instructional Objective The students should understand the formulation of multi-agent search and in detail two-agent search. Students should b familiar
More informationSimple Path Planning Algorithm for Two-Wheeled Differentially Driven (2WDD) Soccer Robots
Simple Path Planning Algorithm for Two-Wheeled Differentially Driven (2WDD) Soccer Robots Gregor Novak 1 and Martin Seyr 2 1 Vienna University of Technology, Vienna, Austria novak@bluetechnix.at 2 Institute
More informationKnowledge Representation and Cognition in Natural Language Processing
Knowledge Representation and Cognition in Natural Language Processing Gemignani Guglielmo Sapienza University of Rome January 17 th 2013 The European Projects Surveyed the FP6 and FP7 projects involving
More informationArtificial Intelligence Adversarial Search
Artificial Intelligence Adversarial Search Adversarial Search Adversarial search problems games They occur in multiagent competitive environments There is an opponent we can t control planning again us!
More informationCognitive Robotics 2016/2017
Cognitive Robotics 2016/2017 Course Introduction Matteo Matteucci matteo.matteucci@polimi.it Artificial Intelligence and Robotics Lab - Politecnico di Milano About me and my lectures Lectures given by
More informationNCCT IEEE PROJECTS ADVANCED ROBOTICS SOLUTIONS. Latest Projects, in various Domains. Promise for the Best Projects
NCCT Promise for the Best Projects IEEE PROJECTS in various Domains Latest Projects, 2009-2010 ADVANCED ROBOTICS SOLUTIONS EMBEDDED SYSTEM PROJECTS Microcontrollers VLSI DSP Matlab Robotics ADVANCED ROBOTICS
More informationMulti-robot Formation Control Based on Leader-follower Method
Journal of Computers Vol. 29 No. 2, 2018, pp. 233-240 doi:10.3966/199115992018042902022 Multi-robot Formation Control Based on Leader-follower Method Xibao Wu 1*, Wenbai Chen 1, Fangfang Ji 1, Jixing Ye
More informationNeural Models for Multi-Sensor Integration in Robotics
Department of Informatics Intelligent Robotics WS 2016/17 Neural Models for Multi-Sensor Integration in Robotics Josip Josifovski 4josifov@informatik.uni-hamburg.de Outline Multi-sensor Integration: Neurally
More informationCS 4700: Foundations of Artificial Intelligence
CS 4700: Foundations of Artificial Intelligence selman@cs.cornell.edu Module: Adversarial Search R&N: Chapter 5 1 Outline Adversarial Search Optimal decisions Minimax α-β pruning Case study: Deep Blue
More informationINTRODUCTION TO ROBOTICS
INTRODUCTION TO ROBOTICS ROBOTICS CLUB SCIENCE AND TECHNOLOGY COUNCIL, IIT-KANPUR AUGUST 6 TH, 2016 OUTLINE What is a robot? Classifications of Robots What goes behind making a robot? Mechanical Electrical
More informationRobotics and Automation Software Developer
Robotics and Automation Software Developer Do the words robotics, Advanced Kinematics, and Artificial Intelligence excite you? Are you driven to discover software solutions to robotics problems that robotics
More informationFormation and Cooperation for SWARMed Intelligent Robots
Formation and Cooperation for SWARMed Intelligent Robots Wei Cao 1 Yanqing Gao 2 Jason Robert Mace 3 (West Virginia University 1 University of Arizona 2 Energy Corp. of America 3 ) Abstract This article
More informationRetaining Learned Behavior During Real-Time Neuroevolution
Retaining Learned Behavior During Real-Time Neuroevolution Thomas D Silva, Roy Janik, Michael Chrien, Kenneth O. Stanley and Risto Miikkulainen Department of Computer Sciences University of Texas at Austin
More informationArtificial Intelligence
Artificial Intelligence CS482, CS682, MW 1 2:15, SEM 201, MS 227 Prerequisites: 302, 365 Instructor: Sushil Louis, sushil@cse.unr.edu, http://www.cse.unr.edu/~sushil Non-classical search - Path does not
More informationArtificial Intelligence: An overview
Artificial Intelligence: An overview Thomas Trappenberg January 4, 2009 Based on the slides provided by Russell and Norvig, Chapter 1 & 2 What is AI? Systems that think like humans Systems that act like
More informationFurther Evolution of a Self-Learning Chess Program
Further Evolution of a Self-Learning Chess Program David B. Fogel Timothy J. Hays Sarah L. Hahn James Quon Natural Selection, Inc. 3333 N. Torrey Pines Ct., Suite 200 La Jolla, CA 92037 USA dfogel@natural-selection.com
More informationUNIT 13A AI: Games & Search Strategies. Announcements
UNIT 13A AI: Games & Search Strategies 1 Announcements Do not forget to nominate your favorite CA bu emailing gkesden@gmail.com, No lecture on Friday, no recitation on Thursday No office hours Wednesday,
More informationEE631 Cooperating Autonomous Mobile Robots. Lecture 1: Introduction. Prof. Yi Guo ECE Department
EE631 Cooperating Autonomous Mobile Robots Lecture 1: Introduction Prof. Yi Guo ECE Department Plan Overview of Syllabus Introduction to Robotics Applications of Mobile Robots Ways of Operation Single
More informationGame Tree Search 1/6/17
Game Tree Search /6/7 Frameworks for Decision-Making. Goal-directed planning Agents want to accomplish some goal. The agent will use search to devise a plan.. Utility maximization Agents ascribe a utility
More informationArtificial Intelligence: Implications for Autonomous Weapons. Stuart Russell University of California, Berkeley
Artificial Intelligence: Implications for Autonomous Weapons Stuart Russell University of California, Berkeley Outline Remit [etc] AI in the context of autonomous weapons State of the Art Likely future
More informationApplication Areas of AI Artificial intelligence is divided into different branches which are mentioned below:
Week 2 - o Expert Systems o Natural Language Processing (NLP) o Computer Vision o Speech Recognition And Generation o Robotics o Neural Network o Virtual Reality APPLICATION AREAS OF ARTIFICIAL INTELLIGENCE
More informationWhat We Talk About When We Talk About AI
MAGAZINE What We Talk About When We Talk About AI ARTIFICIAL INTELLIGENCE TECHNOLOGY 30 OCT 2015 W e have all seen the films, read the comics or been awed by the prophetic books, and from them we think
More informationRobo-Erectus Jr-2013 KidSize Team Description Paper.
Robo-Erectus Jr-2013 KidSize Team Description Paper. Buck Sin Ng, Carlos A. Acosta Calderon and Changjiu Zhou. Advanced Robotics and Intelligent Control Centre, Singapore Polytechnic, 500 Dover Road, 139651,
More informationarxiv: v1 [cs.ai] 7 Nov 2017
arxiv:1711.03580v1 [cs.ai] 7 Nov 2017 First Results from Using Game Refinement Measure and Learning Coefficient in Scrabble Suwanviwatana Kananat s.kananat@jaist.ac.jp July 6, 2018 Abstract Hiroyuki Iida
More informationData-Starved Artificial Intelligence
Data-Starved Artificial Intelligence Data-Starved Artificial Intelligence This material is based upon work supported by the Assistant Secretary of Defense for Research and Engineering under Air Force Contract
More informationAndroid Phone Based Assistant System for Handicapped/Disabled/Aged People
IJIRST International Journal for Innovative Research in Science & Technology Volume 3 Issue 10 March 2017 ISSN (online): 2349-6010 Android Phone Based Assistant System for Handicapped/Disabled/Aged People
More informationAppendices master s degree programme Artificial Intelligence
Appendices master s degree programme Artificial Intelligence 2015-2016 Appendix I Teaching outcomes of the degree programme (art. 1.3) 1. The master demonstrates knowledge, understanding and the ability
More informationIMPROVING TOWER DEFENSE GAME AI (DIFFERENTIAL EVOLUTION VS EVOLUTIONARY PROGRAMMING) CHEAH KEEI YUAN
IMPROVING TOWER DEFENSE GAME AI (DIFFERENTIAL EVOLUTION VS EVOLUTIONARY PROGRAMMING) CHEAH KEEI YUAN FACULTY OF COMPUTING AND INFORMATICS UNIVERSITY MALAYSIA SABAH 2014 ABSTRACT The use of Artificial Intelligence
More informationTraining a Neural Network for Checkers
Training a Neural Network for Checkers Daniel Boonzaaier Supervisor: Adiel Ismail June 2017 Thesis presented in fulfilment of the requirements for the degree of Bachelor of Science in Honours at the University
More informationElectrical and Automation Engineering, Fall 2018 Spring 2019, modules and courses inside modules.
Electrical and Automation Engineering, Fall 2018 Spring 2019, modules and courses inside modules. Period 1: 27.8.2018 26.10.2018 MODULE INTRODUCTION TO AUTOMATION ENGINEERING This module introduces the
More informationMulti-Platform Soccer Robot Development System
Multi-Platform Soccer Robot Development System Hui Wang, Han Wang, Chunmiao Wang, William Y. C. Soh Division of Control & Instrumentation, School of EEE Nanyang Technological University Nanyang Avenue,
More informationJournal Title ISSN 5. MIS QUARTERLY BRIEFINGS IN BIOINFORMATICS
List of Journals with impact factors Date retrieved: 1 August 2009 Journal Title ISSN Impact Factor 5-Year Impact Factor 1. ACM SURVEYS 0360-0300 9.920 14.672 2. VLDB JOURNAL 1066-8888 6.800 9.164 3. IEEE
More informationMaster Artificial Intelligence
Master Artificial Intelligence Appendix I Teaching outcomes of the degree programme (art. 1.3) 1. The master demonstrates knowledge, understanding and the ability to evaluate, analyze and interpret relevant
More information