Conflicts in teamwork: hybrids to the rescue

Today within the AAMAS community, we see at least four competing approaches to building multiagent systems: belief-desire-intention (BDI), distributed constraint optimization (DCOP), distributed POMDPs, and auctions or game-theoretic approaches. While there is exciting progress within each approach, there is a lack of cross-cutting research. This paper highlights hybrid approaches for multiagent teamwork. In particular, for the past decade, the TEAMCORE research group has focused on building agent teams in complex, dynamic domains. While our early work was inspired by BDI, we will present an overview of recent research that uses DCOPs and distributed POMDPs in building agent teams. While DCOP and distributed POMDP algorithms provide promising results, hybrid approaches help us address problems of scalability and expressiveness. For example, in the BDI-POMDP hybrid approach, BDI team plans are exploited to improve POMDP tractability, and POMDPs improve BDI team plan performance. We present some recent results from applying this approach in a Disaster Rescue simulation domain being developed with help from the Los Angeles Fire Department.

[1]  Milind Tambe,et al.  Building Dynamic Agent Organizations in Cyberspace , 2000, IEEE Internet Comput..

[2]  Milind Tambe,et al.  Valuations of Possible States (VPS): a quantitative framework for analysis of privacy loss among collaborative personal assistant agents , 2005, AAMAS '05.

[3]  Sarit Kraus,et al.  Collaborative Plans for Complex Group Action , 1996, Artif. Intell..

[4]  Steven Minton,et al.  Minimizing Conflicts: A Heuristic Repair Method for Constraint Satisfaction and Scheduling Problems , 1992, Artif. Intell..

[5]  Milind Tambe,et al.  Two Fielded Teams and Two Experts: A RoboCup Challenge Response from the Trenches , 1999, IJCAI.

[6]  Makoto Yokoo,et al.  Taming Decentralized POMDPs: Towards Efficient Policy Computation for Multiagent Settings , 2003, IJCAI.

[7]  Sarit Kraus,et al.  Towards a formalization of teamwork with resource constraints , 2004, Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, 2004. AAMAS 2004..

[8]  Milind Tambe,et al.  How local is that optimum? k-optimality for DCOP , 2005, AAMAS '05.

[9]  Makoto Yokoo,et al.  Distributed constraint satisfaction algorithm for complex local problems , 1998, Proceedings International Conference on Multi Agent Systems (Cat. No.98EX160).

[10]  Milind Tambe,et al.  Hybrid BDI-POMDP Framework for Multiagent Teaming , 2011, J. Artif. Intell. Res..

[11]  Milind Tambe,et al.  A prototype infrastructure for distributed robot-agent-person teams , 2003, AAMAS '03.

[12]  Milind Tambe,et al.  Distributed Algorithms for DCOP: A Graphical-Game-Based Approach , 2004, PDCS.

[13]  Milind Tambe,et al.  Preprocessing techniques for accelerating the DCOP algorithm ADOPT , 2005, AAMAS '05.

[14]  Neil Immerman,et al.  The Complexity of Decentralized Control of Markov Decision Processes , 2000, UAI.

[15]  Milind Tambe,et al.  Robust Agent Teams via Socially-Attentive Monitoring , 2000, J. Artif. Intell. Res..

[16]  M. Yokoo,et al.  Distributed Breakout Algorithm for Solving Distributed Constraint Satisfaction Problems , 1996 .

[17]  Weixiong Zhang,et al.  Towards flexible teamwork in persistent teams , 1998, Proceedings International Conference on Multi Agent Systems (Cat. No.98EX160).

[18]  Milind Tambe,et al.  Towards Flexible Teamwork , 1997, J. Artif. Intell. Res..

[19]  Milind Tambe,et al.  Towards Adjustable Autonomy for the Real World , 2002, J. Artif. Intell. Res..

[20]  Milind Tambe,et al.  Intelligent Agents for Interactive Simulation Environments , 1995, AI Mag..

[21]  Tamer Basar,et al.  Coalition formation in proportionally fair divisible auctions , 2003, AAMAS '03.

[22]  Makoto Yokoo,et al.  Adopt: asynchronous distributed constraint optimization with quality guarantees , 2005, Artif. Intell..

[23]  Milind Tambe,et al.  DCOP Games for Multi-agent Coordination , 2005 .

[24]  Milind Tambe,et al.  Exploiting belief bounds: practical POMDPs for personal assistant agents , 2005, AAMAS '05.

[25]  Makoto Yokoo,et al.  Networked Distributed POMDPs: A Synergy of Distributed Constraint Optimization and POMDPs , 2005, IJCAI.

[26]  Milind Tambe,et al.  Demonstration of DEFACTO: training tool for incident commanders , 2005, AAMAS '05.

[27]  Roger Mailler Comparing two approaches to dynamic, distributed constraint satisfaction , 2005, AAMAS '05.

[28]  Makoto Yokoo,et al.  Distributed Multi-Criteria Coordination in Multi-Agent Systems , 2005 .

[29]  Wei-Min Shen,et al.  A Dynamic Distributed Constraint Satisfaction Approach to Resource Allocation , 2001, CP.

[30]  Milind Tambe,et al.  Distributed Sensor Networks: A Multiagent Perspective , 2003 .

[31]  Milind Tambe,et al.  An Automated Teamwork Infrastructure for Heterogeneous Software Agents and Humans , 2003, Autonomous Agents and Multi-Agent Systems.

[32]  John Yen,et al.  CAST: Collaborative Agents for Simulating Teamwork , 2001, IJCAI.

[33]  John P. Lewis,et al.  The DEFACTO System: Training Tool for Incident Commanders , 2005, AAAI.

[34]  Allocating Tasks in Extreme Teams Paper Tracking Number : 469 , 2004 .

[35]  Hector J. Levesque,et al.  On Acting Together , 1990, AAAI.

[36]  Weixiong Zhang,et al.  Towards Flexible Teamwork in Persistent Teams: Extended Report , 2000, Autonomous Agents and Multi-Agent Systems.

[37]  Milind Tambe,et al.  Monitoring Teams by Overhearing: A Multi-Agent Plan-Recognition Approach , 2002, J. Artif. Intell. Res..