Intelligent Agents: Technology and Applications Agent Teamwork IST 597B Spring 2003 John Yen.

Slides:



Advertisements
Similar presentations
Pat Langley Computational Learning Laboratory Center for the Study of Language and Information Stanford University, Stanford, California USA
Advertisements

DELOS Highlights COSTANTINO THANOS ITALIAN NATIONAL RESEARCH COUNCIL.
Twelve Cs for Team Building
12 August 2004 Strategic Alignment By Maria Rojas.
Team Structure The ratio of We’s to I’s is the best indicator of the development of a team. –Lewis B. Ergen NEXT: ®
ARCHITECTURES FOR ARTIFICIAL INTELLIGENCE SYSTEMS
JSIMS 28-Jan-99 1 JOINT SIMULATION SYSTEM Modeling Command and Control (C2) with Collaborative Planning Agents Randall Hill and Jonathan Gratch University.
UML (Sequence Diagrams, Collaboration and State Chart Diagrams) Presentation By - SANDEEP REDDY CHEEDEPUDI (Student No: ) - VISHNU CHANDRADAS (Student.
OASIS Reference Model for Service Oriented Architecture 1.0
Effective Coordination of Multiple Intelligent Agents for Command and Control The Robotics Institute Carnegie Mellon University PI: Katia Sycara
TEXAS A&M UNIVERSITY AND THE UNIVERSITY OF TEXAS AT AUSTIN Army Digitization Research Initiative Dr. Richard A. Volz (Computer Science) Dr. Tom Ioerger.
Agent Mediated Grid Services in e-Learning Chun Yan, Miao School of Computer Engineering Nanyang Technological University (NTU) Singapore April,
Distribution decisions in international context External factors Structure of distribution/channel Conflict & Control issues Managing logistics.
A Decision-Theoretic Approach to Designing Proactive Communication in Multi-Agent Teamwork Thomas R. Ioerger, Yu Zhang, Richard Volz, John Yen (PSU-IST)
Introduction and Overview “the grid” – a proposed distributed computing infrastructure for advanced science and engineering. Purpose: grid concept is motivated.
Modeling Teamwork in the CAST Multi-Agent System Thomas R. Ioerger Department of Computer Science Texas A&M University.
Teamwork IE491 October 17, Teamwork thoughts What do you think of when I say teamwork? How many of you have participated in a team-oriented activity?
© 2005 Prentice-Hall 8-1 Understanding Work Teams Chapter 8 Essentials of Organizational Behavior, 8/e Stephen P. Robbins.
01 -1 Lecture 01 Intelligent Agents TopicsTopics –Definition –Agent Model –Agent Technology –Agent Architecture.
Modeling Teamwork in Multi-Agent Systems: The CAST Architecture Dr. Thomas Ioerger, Jianwen Yin, and Michael Miller Computer Science, Texas A&M University.
IE496 Industrial Engineering Internship Dr. Barnes October 16, 2006 Lecture #6.
Texas A&M University CAST: Collaborative Agents for Simulating Teamwork John Yen, Jianwen Yin, Thomas R. Ioerger, Michael Miller, Dianxiang Xu, Richard.
Course Instructor: Aisha Azeem
Coaching Workshop.
Organizational Behavior MBA-542 Instructor: Erlan Bakiev, Ph.D.
+ Session 3: Supporting Change + Tonight’s Topics Supporting Change: Why do people resist change?? Why do people change? How do we support change MANAGING.
An Intelligent Broker Architecture for Context-Aware Systems A PhD. Dissertation Proposal in Computer Science at the University of Maryland Baltimore County.
Team Building.
COMP3615/5615 Capstone Projects
Learning HMM-based cognitive load models for supporting human-agent teamwork Xiaocong Fan, Po-Chun Chen, John Yen 소프트컴퓨팅연구실황주원.
Coalition Formation between Self-Interested Heterogeneous Actors Arlette van Wissen Bart Kamphorst Virginia DignumKobi Gal.
Intelligent Software Agents Lab The Robotics Institute Carnegie Mellon University 5000 Forbes Avenue Pittsburgh, PA (U.S.A.)
Team Structure The ratio of We’s to I’s is the best indicator of the development of a team. –Lewis B. Ergen NEXT: ™
Chapter 10 THE NATURE OF WORK GROUPS AND TEAMS. CHAPTER 10 The Nature of Work Groups and Teams Copyright © 2002 Prentice-Hall What is a Group? A set of.
Team Formation between Heterogeneous Actors Arlette van Wissen Virginia Dignum Kobi Gal Bart Kamphorst.
INFO3600 Capstone Projects Week This lab and week Group work terminology based on Big-5 – Cf. XP roles and methods First user stories Research.
L 9 : Collaborations Why? Terminology Coherence Coordination Reference s :
High Level Architecture Overview and Rules Thanks to: Dr. Judith Dahmann, and others from: Defense Modeling and Simulation Office phone: (703)
Understanding Work Teams
Travis Steel. Objectives What is the Agent Paradigm? What is Agent-Oriented Design and how is it different than OO? When to apply AOD techniques? When.
What is a Business Analyst? A Business Analyst is someone who works as a liaison among stakeholders in order to elicit, analyze, communicate and validate.
Feb 24, 2003 Agent-based Proactive Teamwork John Yen University Professor of IST School of Information Sciences and Technology The Pennsylvania State University.
ARTIFICIAL INTELLIGENCE [INTELLIGENT AGENTS PARADIGM] Professor Janis Grundspenkis Riga Technical University Faculty of Computer Science and Information.
NAVEEN AGENT BASED SOFTWARE DEVELOPMENT. WHAT IS AN AGENT? A computer system capable of flexible, autonomous (problem-solving) action, situated in dynamic,
Identity Management: A Technical Perspective Richard Cissée DAI-Labor; Technische Universität Berlin
Intelligent Agents RMIT Prof. Lin Padgham (leader) Ass. Prof. Michael Winikoff Ass. Prof James Harland Dr Lawrence Cavedon Dr Sebastian Sardina.
Team Structure The ratio of We’s to I’s is the best indicator of the development of a team. –Lewis B. Ergen NEXT:
Information & Decision Superiority Case studies in applying AI planning technologies to military & civil applications Dr Roberto Desimone Innovations.
Christoph F. Eick University of Houston Organization 1. What are Ontologies? 2. What are they good for? 3. Ontologies and.
Understanding Work Teams
Stephen P. Robbins & Timothy A. Judge
Artificial Immune System based Cooperative Strategies for Robot Soccer Competition International Forum on Strategic Technology, p.p , Oct
Dynamic Synthesis of Mediators in Pervasive Environments Amel Bennaceur supervised by Valérie Issarny ARLES 14 February 2012, Junior Seminar, INRIA.
Multiagent System Katia P. Sycara 일반대학원 GE 랩 성연식.
1 1 Chapter 10 Marketing Channels: Delivering Customer Value.
The Architecture of Systems. System Architecture Every human-made and natural system is characterized by a structure and framework that supports and/or.
P.Bernus 1999 New Applications Of GERAM to Virtual Enterprises And Networks Peter Bernus Griffith University June, 1999.
Intelligent Agents. 2 What is an Agent? The main point about agents is they are autonomous: capable of acting independently, exhibiting control over their.
Service Brokering Yu-sik Park. Index Introduction Brokering system Ontology Services retrieval using ontology Example.
Unit 1: Health IT Teams Examples and Characteristics Component 17/ Unit 11 Health IT Workforce Curriculum Version 1.0/Fall 2010.
Copyright © 2012 Pearson Canada Inc. 00 Chapter 11 Alliances as Vehicles.
Semantic Web in Context Broker Architecture Presented by Harry Chen, Tim Finin, Anupan Joshi At PerCom ‘04 Summarized by Sungchan Park
McGraw-Hill/Irwin© 2005 The McGraw-Hill Companies, Inc. All rights reserved Chapter8 Groups Behavior and Teamwork.
Intelligent Agents: Technology and Applications Unit Five: Collaboration and Task Allocation IST 597B Spring 2003 John Yen.
SRA 2016 – Strategic Research Challenges Design Methods, Tools, Virtual Engineering Jürgen Niehaus, SafeTRANS.
MGT 6500: Managing Individuals & Groups
Thrust IC: Action Selection in Joint-Human-Robot Teams
Fostering Relational Exchange with the Internet
Presentation transcript:

Intelligent Agents: Technology and Applications Agent Teamwork IST 597B Spring 2003 John Yen

Learning Objectives:  Given an application that involves a group of agents, be able to identify its major characteristics (e.g., adhoc vs structured team etc).  For a specific types of agent team applications, be able to identify major issues related to the design of such agent teams.  Given an agent team applications, be able to determine whether a particular agent teamwork model/architecture (i.e., CAST) is suitable for the application.

Problem 1 Consider the following five applications involving agent teams, identify several key characteristics that are important for these applications. Use a table to compare the similarities and differences of these applications along these characteristics.

1. A team of agents that play Robot Soccer together. 2. A team including robots, soldiers, and software agents (for information fusion/delivery) in the battle field. 3. A team of software agents that support/automate the information exchanges and/or transactions of business partners (e.g., supplier of parts, manufacturers of products, distributors,...) in a supply chain. 4. A group of agents that assist the companies they each represent to form coalitions for business opportunities. 5. A group of agents, each represent a user, interacts in an e-auction marketplace.

Characteristics  Team membership: Static vs dynamic  Shared goals vs individual goals  Benevolent vs selfish  Hierarchical vs Egalitarian  Homogenous vs Heterogeneous  Level of Trust  Coordination vs competition

Key Characteristics for Agent Teamwork  Benevolent (shared goals) vs selfish (individual goals)  Capabilities: Homogenous vs Heterogeneous  Membership of the Team: Static vs dynamic  Structure of the Team: Completely predefined, partially defined by roles, completely unspecified.  Types of the structure: Hierarchical vs Egalitarian  Process of the Team: Completely predetermined, partially specified, dynamically generated.  Human agent-software agent relationship: boss-assistant, peer, trainee-coach.  Relationship between members of the Group: Cooperative, partially cooperative, competitive.  The level of trust

Homework 3 (15%, team assignment, due April 8th) Compare the similarities and differences of the five agent teams using the key characteristics identified in class. Describe a (sixth) agent team application and characterize it using the characteristics.

Problem 2: (5%)  What are important issues related to these characteristics?

Related Issues - Team Structure  How to form a team? How to determine the structure of a team? –Important if the structure of the team is dynamically determined.  How to specify roles and assign responsibilities based on roles? –Important if the team structure is partially specified by roles.  How to reconfigure a team? –Important if members of the team may die or be overloaded  How to resolve conflicts in a team? –Important if the team does not have a hierarchical structure.

Related Issues - Team Process  How to specify, coordinate, and execute a team process? –If the process is partially/fully specified.  How to generate a team process (through planning)? –If the process is dynamically generated.  How to make sure emergent behavior achieves expected effects? –If the process is not specified.

Related Issues - Human-agent Relationship  How to give human users adequate control of agents? –If agents are assistant to human  How to enable agents to understand the mental states of human and the context of the interactions? –If agents are peer; and (to some degree) assistant.  How much can users trust agents?  How to design friendly interface to enables agents and user interact more effectively?  How to make agents human-like?

Related Issues - Cooperative/Competitive  How to enable agents to negotiate with others? –If agents are partially cooperative partially competitive  How does an agent balance intentions of others with intentions of self when they are conflicting. –If agents are not selfish less (I.e., partially self-centered).

Related Issues - Trust  How to establish/guarantee/revise trust? –Important if trust is important

Two Conflicting Objectives of Teamwork Models  Efficiency –Higher team performance –Reduced communications  Flexibility/Adaptability –Adapt the structure of the team –Adapt the process of the team –Adapt the responsibility assignment

Goals for CAST Teamwork Model  Achieves a high-level of efficiency with a reasonable degree of adaptability for applications with role-based structure and process.

Motivation Psychological Studies about Effective Human Teamwork Indicated that  Team members can anticipate needs of team mates  Team members can offer relevant information proactively.  These teamwork behaviors are based on an overlapping shared mental model.

Shared Mental Model  Shared Ontology  Shared Goals  Shared Team Structure  Shared Team Collaboration Process  Shared Belief about the Team  Shared Belief about the World –Shared Hypotheses about the Enemy

CAST Agent Architecture  Use a high-level language to describe teamwork knowledge  Capture “shared mental model” about team structure and process  Infers information needs (from SMM)  induces proactive information exchanges

Anticipating Information Needs of Teammates Team Plan Responsibilities of Tasks Preconditions of Tasks Information Needs Dynamic Task Allocation Who needs what

Dynamic Task Allocation Team Plan Constraints for Task Allocation Roles of Agents in the Team My Belief about The World My Belief about Teammates Dynamic Task Allocation

Proactive Information Delivery My Belief about Teammates Information Needs Information Match ? Communication Strategy Does he/she know ? How to inform him/her?

CAST Agent Architecture Team Knowledge (MALLET) Responsibilities (Petri Nets) Belief Domain Knowledge Responsibility Selection Identify Info Needs Information Needs Information Belief Update Act on Info Needs

Shared Mental Model in CAST  Prolog knowledge base: belief  MALLET: High-level language for representing team knowledge  Petri Nets: An agent’s internal representation of the dynamic teamwork processes and related information requirements

Relationships between SMM Components MALLET Knowledge Base Prolog Knowledge Base (belief) MALLET Compiler Petri Net (team process) query reply CAST Kernel

(team-plan T1 () (process (par (kill-wumpuses) (collect-gold)))) (team-plan kill-wumpuses () (agent-bind ?s (play-role ?s scout)) (agent-bind ?f (play-role ?f fighter)(closest ?f wumpus)) (process (while ((wumpus ?x) (not (dead ?x)))) (seq (do ?s (find-wumpus ?x)) (do ?f (move-to-wumpus ?x)) (do ?f (shoot-wumpus ?x))))) (team-plan find-gold () (agent-bind ?c (play-role ?c carrier)) (process (while (true) (if (see ?any-agent glitter) (do ?c (carrier-pickup gold)))) start findshootmove wumpus exists glitter done no wumpuses left pickup

CAST Development Environ. Circles are places and hold tokens denoting current execution state. Red indicates the presence of a token. Rectangles are transitions and are tested and executed when preceding places have tokens.

Two Types of Information needs  Action-performing information needs –enables an agent to perform certain (complex) actions, which contributes to an agent's individual commitments to the whole team.  Goal-protection information needs –allows an agent to protect a goal from potential threats that may result in a conflict with the goal.

Applications  Training for AWACS-like synthetic task (AFOSR MURI)  Support Agent-based Collaborative Mission Planning (Army Research Lab)  Simulating Digital TOC (STRICOM)  Negotiation among Agent Teams for Engineering Design (NSF)

Conclusion  A computational shared mental model is critical for developing agents that support a team involving both agents and human.  (PSU-TAMU) CAST enables proactive information delivery by anticipating needs of teammates.  MALLET facilitates the reuse of teamwork knowledge  CAST achieves efficiency using shared team plans and shared policy  CAST achieves adaptability by dynamic assignment of agent responsibility