CSI6558 Software Agent(Intelligent and Cognitive Agents)

Spring Semester, 2009

Dept. of Computer Science

Yonsei University

Course Objectives

introduce the student to the concept of an agent and cognitive system, and the main applications for which they are appropriate;

introduce the main issues surrounding the design of intelligent agents;

introduce the main issues surrounding the design of a cognitive system; and

introduce a contemporary platform for implementing agents and cognitive systems.

Learning Outcomes

Upon completing this course, a student will:

– understand the notion of an agent, how agents are distinct from other software paradigms (e.g., objects), and understand the characteristics of applications that lend themselves to an agent-oriented solution;

– understand the key issues associated with constructing agents capable of intelligent autonomous action, and the main approaches taken to developing such agents;

– understand the key issues in designing societies of agents that can effectively cooperate in order to solve problems, including an understanding of the key types of cognitive capabilities possible in such systems;

– understand the main application areas of agent-based solutions, and be able to develop a meaningful agent-based system using a contemporary agent development platform.

Contact

Instructor

– Prof. Sung-Bae Cho (Eng. C515; 2123-2720; sbcho@cs.yonsei.ac.kr)

Web-page : http://sclab.yonsei.ac.kr/Courses/09Agent

Class hours

– Tue 11:00 ~ 11:50, Thu 11:00~12:50 (Eng. A542, A646)

Office hour

– The 17:00 ~ 19:00

TA

– Dr. Jin-Hyuk Hong / Mr. Sungsoo Lim (hjinh@sclab.yonsei.ac.kr)

Textbook– Readings in Software Agents

References – [Woo] M. Wooldridge, An Introduction to MultiAgent Systems. John

Wiley & Sons, 2002. ISBN 0 47149691X.– Jeffrey M. Bradshaw (Ed), Software Agents, MIT Press, 1997– Michael N. Huhns, Munindar P. Singh, Readings in Agents, Morgan

Kaufmann, 1998– Jacques Ferber, Multi-Agent Systems, Addison-Wesley, 1999– Akira Namatame (Ed), Agent-based Approaches in Economic and

Social Complex Systems, 2002– Related Conference Proceedings (IJCAI, AAAI, PRICAI, IAT, etc)– UMBC site : http://agents.umbc.edu/– MIT site : http://ttt.media.mit.edu/research/research.html– SAT site : http://www.cs.uta.fi/sat/materials

Course Materials

Course Schedule

주차 Topics 비고1 강의소개2 지능형 에이전트 : 개요3 지능형 에이전트 : 핵심 기술4 지능형 에이전트 : 인지구조5 인지기반 지능형 에이전트 설계 : 인식 (1) 주의집중 , 의식 , 언어 등6 인지기반 지능형 에이전트 설계 : 인식 (2) 주의집중 , 의식 , 언어 등7 프로젝트 제안서 발표8 중간시험 기간

9 인지기반 지능형 에이전트 설계 : 기억 동작 메모리 , 에피소딕 및 시멘틱

메모리10 인지기반 지능형 에이전트 설계 : 학습 강화학습11 인지기반 지능형 에이전트 설계 : 기타 감성 , 소셜 인지 등12 지능형 에이전트 응용 : 추천 에이전트13 지능형 에이전트 응용 : 게임 에이전트

14 지능형 에이전트 응용 : 대화 / 감성

에이전트15 프로젝트 결과 발표16 기말시험 기간

Papers: Cognitive Capabilities (1)

4 주차 : 인지구조– Cognitive architectures: Research issues and challenges, Cognitive Systems Research, 2009.– Theoretical status of computational cognitive modeling, Cognitive Systems Research, 2009.– Human symbol manipulation within an integrated cognitive architecture, Cognitive Science,

2005.– The importance of cognitive architectures: An analysis based on CLARION, Journal of

Experimental and Theoretical Artificial Intelligence, 2007.– A Gentle Introduction to Soar: 2006 update, 2006.

5 주차 : 인지기반 지능형 에이전트 설계 : 인식 (1)– A computational neuroscience approach to consciousness, Neural Networks, 2007.– A model of agent consciousness and its implementation, Neurocomputing, 2006.– A Neural Global Workspace Model for Conscious Attention, Neural Networks, 1997.– Computational studies of consciousness, Progress in Brain Research, 2008.

6 주차 : 인지기반 지능형 에이전트 설계 : 인식 (2)– Associative computer: a hybrid connectionistic production system, Cognitive Systems

Research, 2005.– Attention as a controller, Neural Networks, 2006.– Global workspace theory of consciousness: toward a cognitive neuroscience of human

experience, Progress in Brain Research, 2005.– Progress in machine consciousness, Consciousness and Cognition, 2008.

Papers: Cognitive Capabilities (2) 7 주차 : 인지기반 지능형 에이전트 설계 : 기억

– How conscious experience and working memory interact, Trends in Cognitive Sciences, 2003.– Probabilistic inference in human semantic memory, Trends in Cognitive Sciences, 2006.– Sparse distributed memory for ‘conscious’ software agents, Cognitive Systems Research, 2003.– Pre-frontal executive committee for perception, working memory, attention, long-term memory, motor

control, and thinking: A tutorial review, Consciousness and Cognition, 2003. 8 주차 : 인지기반 지능형 에이전트 설계 : 학습

– Emergence of self-organized symbol-based communication in artificial creatures, Cognitive Systems Research, 2009.

– Hybridizing evolutionary computation and reinforcement learning for the design of almost universal controllers for autonomous robots, Neurocomputing, 2009.

– Learning HMM-based cognitive load models for supporting human-agent teamwork, Cognitive Systems Research, 2009.

– Application of reinforcement learning to the game of Othello, Computers & Operations Research, 2008. 11 주차 : 인지기반 지능형 에이전트 설계 : 기타

– A computational unification of cognitive behavior and emotion, Cognitive Systems Research, 2009.– A conceptual and empirical framework for the social distribution of cognition: The case of memory,

Cognitive Systems Research, 2008.– Affective guidance of intelligent agents: How emotion controls cognition, Cognitive Systems Research,

2009.– Google home: Experience, support and re-experience of social home activities, Information Science, 2008.

Papers: Application 12 주차 : 지능형 에이전트 응용 : 추천 / 멀티 에이전트

– A cognitive approach for agent-based personalized recommendation, Knowledge-Based Systems, 2007.

– An ontology, intelligent agent-based framework for the provision of semantic web services, Expert Systems with Applications, 2009.

– A synthetical approach for blog recommendation: Combining trust, social relation, and semantic analysis, Expert Systems with Applications, 2009.

– Building an expert travel agent as a software agent, Expert Systems with Applications, 2009. 13 주차 : 지능형 에이전트 응용 : 게임 에이전트

– Knowledge acquisition for adaptive game AI, Science of Computer Programming, 2007.– Coevolution versus self-play temporal difference learning for acquiring position evaluation in small-

board go, IEEE TEC, 2005.– Generating Ambient Behaviors in Computer Role-Playing Games, IEEE Intelligent Systems, 2006.– Teaming up humans with autonomous synthetic characters, Artificial Intelligence, 2009.

14 주차 : 지능형 에이전트 응용 : 대화 / 감성 에이전트– A BDI approach to infer student’s emotions in an intelligent learning environment, Computers &

Education, 2007.– Emotional agents: A modeling and an application, Information and Software Technology, 2007.– Fully generated scripted dialogue for embodied agents, Artificial Intelligence, 2008.– Intentional systems: Review of neurodynamics, modeling, and robotics implementation, Physics of Life

Reviews, 2008.

Evaluation Criteria

Evaluation Criteria

– Term Project (written report and an oral presentation) : 50%

– Presentation : 30%

– Homeworks and Class Participation : 20%

Term Project (Oral presentation is required) :

– Theoretical Issue (Analysis, Experiment, Simulation) : Originality

– Interesting Programming (Game, Demo, etc) : Performance

– Survey : Completeness

List of Possible Projects

Conversational agents Artificial-life agents Intelligent agents for mobile devices Inference and prediction for agents Service discovery agents Game agents Semantic modeling for agents Distributed information agents (Amalthae, Anarchid) Personalized information agents Avatar …

Questions & Answers