Complexity of Coordinating Autonomous Planning Agents

Mors, Adriaan ter; Valk, Jeroen; Witteveen, Cees

doi:10.1007/978-3-540-28633-2_131

Cited by 11 publications

(12 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This number also turns out to be a strict lower bound when proving co-NP-completeness: For FIXCV-instances with 2 or 3 tasks per agent, we can easily show them to be decidable in polynomial time by reducing them to the acyclic graph problem [18].…”

Section: Fixed Coordination Verification (Fixcv) Given a Fixed Task mentioning

confidence: 97%

See 1 more Smart Citation

Coordinating Self-interested Planning Agents

Buzing

Mors

Valk

et al. 2006

Auton Agent Multi-Agent Syst

Self Cite

View full text Add to dashboard Cite

We consider planning problems where a number of non-cooperative agents have to work on a joint problem. Such problems consist in completing a set of interdependent, hierarchically ordered tasks. Each agent is assigned a subset of tasks to perform for which it has to construct a plan. Since the agents are non-cooperative, they insist on planning independently and do not want to revise their individual plans when the joint plan has to be assembled from the individual plans. We present a general formal framework to study some computational aspects of this non-cooperative coordination problem and we establish some complexity results to identify some of the factors that contribute to the complexity of this problem. Finally, we illustrate our approach with an application to coordination in multi-modal logistic planning.

show abstract

Section: Fixed Coordination Verification (Fixcv) Given a Fixed Task mentioning

confidence: 97%

“…Hence, the problem is in p 2 . Hardness for this class is shown by reducing a p 2 -complete quantified version of the PWFP-problem to it [18].…”

Section: Fixed Coordination Verification (Fixcv) Given a Fixed Task mentioning

confidence: 99%

Coordinating Self-interested Planning Agents

Buzing

Mors

Valk

et al. 2006

Auton Agent Multi-Agent Syst

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, temporal constraints can be added to the agents' STNs up front so that they need not communicate at all during scheduling and execution [37]. Another preplanning coordination method adds a minimal set of additional constraints to the subgoals to be performed in order to ensure a coordinated solution by independent planning [60].…”

Section: Coordination Before Planningmentioning

confidence: 99%

Introduction to planning in multiagent systems

Weerdt

Clement

2009

MGS

View full text Add to dashboard Cite

Abstract. In most multiagent systems planning on forehand can help to seriously improve the efficiency of executing actions. The main difference between centrally creating a plan and constructing a plan for a system of agents lies in the fact that in the latter coordination plays the main part. This introduces a number of additional difficulties. This special issue discusses some of these difficulties in detail. To place these in a context, this introduction gives a brief overview of multiagent planning problems, and most multiagent planning techniques.

show abstract

“…There is a long tradition of work on multi-agent planning for cooperative and noncooperative agent teams involving centralized and distributed algorithms, often using involved models that model uncertainty, resources, and more (Conry et al, 1991;Ephrati & Rosenschein, 1997;Hansen & Zilberstein, 2001;Bernstein, Givan, Immerman, & Zilberstein, 2002;Szer, Charpillet, & Zilberstein, 2005;, and much work on how to coordinate the local plans of agents or to allow agents to plan locally under certain constraints (Cox & Durfee, 2005;Steenhuisen, Witteveen, ter Mors, & Valk, 2006;ter Mors, Valk, & Witteveen, 2004;ter Mors & Witteveen, 2005). Our work is influenced and motivated by some of the results in that area, but takes as its starting point a more basic model introduced by Brafman and Domshlak (BD) that offers what is possibly the simplest model of MA planning -ma-strips (Brafman & Domshlak, 2008).…”

Section: Introductionmentioning

confidence: 99%

Distributed Heuristic Forward Search for Multi-agent Planning

Nissim¹,

Brafman²

2014

jair

View full text Add to dashboard Cite

This paper deals with the problem of classical planning for multiple cooperative agents who have private information about their local state and capabilities they do not want to reveal. Two main approaches have recently been proposed to solve this type of problem -one is based on reduction to distributed constraint satisfaction, and the other on partial-order planning techniques. In classical single-agent planning, constraint-based and partial-order planning techniques are currently dominated by heuristic forward search. The question arises whether it is possible to formulate a distributed heuristic forward search algorithm for privacy-preserving classical multi-agent planning. Our work provides a positive answer to this question in the form of a general approach to distributed state-space search in which each agent performs only the part of the state expansion relevant to it. The resulting algorithms are simple and efficient -outperforming previous algorithms by orders of magnitude -while offering similar flexibility to that of forward-search algorithms for single-agent planning. Furthermore, one particular variant of our general approach yields a distributed version of the a* algorithm that is the first cost-optimal distributed algorithm for privacy-preserving planning.

show abstract

Complexity of Coordinating Autonomous Planning Agents

Cited by 11 publications

References 3 publications

Coordinating Self-interested Planning Agents

Coordinating Self-interested Planning Agents

Introduction to planning in multiagent systems

Distributed Heuristic Forward Search for Multi-agent Planning

Contact Info

Product

Resources

About