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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 agentoriented 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;
[email protected])
 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 ([email protected])
Course Materials
 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 Schedule
주차
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Topics
강의소개
지능형 에이전트: 개요
지능형 에이전트: 핵심 기술
지능형 에이전트: 인지구조
인지기반 지능형 에이전트 설계: 인식 (1)
인지기반 지능형 에이전트 설계: 인식 (2)
프로젝트 제안서 발표
중간시험 기간
인지기반 지능형 에이전트 설계: 기억
인지기반 지능형 에이전트 설계: 학습
인지기반 지능형 에이전트 설계: 기타
지능형 에이전트 응용: 추천 에이전트
지능형 에이전트 응용: 게임 에이전트
지능형 에이전트 응용: 대화/감성 에이전트
프로젝트 결과 발표
기말시험 기간
비고
주의집중, 의식, 언어 등
주의집중, 의식, 언어 등
동작 메모리, 에피소딕 및 시멘틱 메모리
강화학습
감성, 소셜 인지 등
Papers: Cognitive Capabilities (1)



4주차: 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.
5주차: 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.
6주차: 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)



7주차: 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.
8주차: 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.
11주차: 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



12주차: 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.
13주차: 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.
14주차: 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)
– Presentation
– Homeworks and Class Participation
: 50%
: 30%
: 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