Communication for Goal Directed Agents

Dastani, Mehdi; Ham, Jeroen van der; Dignum, Frank

doi:10.1007/978-3-540-44972-0_13

Cited by 18 publications

(14 citation statements)

References 5 publications

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“…Fortunately, the 3APL language has been developed precisely to help bridging the gap between theoretical models (in particular, logic-based) and practical implementation of MAS concepts. Since 3APL is well documented and discussed in [4,3,2], we only sum up the basics here. A 3APL agent is made of 6 bases:…”

Section: The Negotiation Protocolmentioning

confidence: 99%

Interest-Based Negotiation as an Extension of Monotonic Bargaining in 3APL

Pasquier

Dignum

Rahwan

et al. 2006

Agent Computing and Multi-Agent Systems

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Abstract. Reframing is a sub-type of interest-based negotiation strategy that enhances bargaining by allowing the negotiators to ask for the underlying goal of the negotiation and propose alternative plan(s) which may entail a deal on alternative issues. This paper (i) presents a negotiation protocol that support both alternate offers monotonic bargaining and reframing and (ii) gives a fully computational and reproducible specification of bargaining and reframing capable negotiation agents using the 3APL agent language.

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Section: The Negotiation Protocolmentioning

confidence: 99%

Interest-Based Negotiation as an Extension of Monotonic Bargaining in 3APL

Pasquier

Dignum

Rahwan

et al. 2006

Agent Computing and Multi-Agent Systems

Self Cite

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“…This is because commitments don't trigger actions directly: they may trigger actions indirectly, but in general their effect is to prevent completion of an interaction while there are outstanding (base level) commitments. Figure 6 shows the message sequences from a number of runs of a 3APL implementation of the NetBill commitment machine 6 . In order to illustrate the different possible interactions the code was modified so that each agent selected randomly from the actions that it could perform, and a number of runs were made with the customer as the initiator, and then with the merchant as the initiator.…”

Section: Figure 5: New Operational Semanticsmentioning

confidence: 99%

Implementing commitment-based interactions

Winikoff

2007

Proceedings of the 6th International Joint Conference on Autonomous Agents and Multiagent Systems

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Although agent interaction plays a vital role in MAS, and messagecentric approaches to agent interaction have their drawbacks, present agent-oriented programming languages do not provide support for implementing agent interaction that is flexible and robust. Instead, messages are provided as a primitive building block. In this paper we consider one approach for modelling agent interactions: the commitment machines framework. This framework supports modelling interactions at a higher level (using social commitments), resulting in more flexible interactions. We investigate how commitmentbased interactions can be implemented in conventional agent-oriented programming languages. The contributions of this paper are: a mapping from a commitment machine to a collection of BDI-style plans; extensions to the semantics of BDI programming languages; and an examination of two issues that arise when distributing commitment machines (turn management and race conditions) and solutions to these problems.

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“…Much work has been done low level communication issues such as agent communication languages and physical implementation of communications [12,13,29]. Pynadath and Tambe have formalized many aspects of agent communications [25], including observability and explicit communication.…”

Section: Communication Among Agentsmentioning

confidence: 99%

Handling Communication Restrictions and Team Formation in Congestion Games

Agogino

Tumer

2006

Auton Agent Multi-Agent Syst

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Abstract. There are many domains in which a multi-agent system needs to maximize a "system utility" function which rates the performance of the entire system, while subject to communication restrictions among the agents. Such communication restrictions make it difficult for agents that take actions to optimize their own "private" utilities to also help optimize the system utility. In this article we show how previously introduced utilities that promote coordination among agents can be modified to be effective in domains with communication restrictions. The modified utilities provide performance improvements of up to 75% over previously used utilities in congestion games (i.e., games where the system utility depends solely on the number of agents choosing a particular action). In addition, we show that in the presence of severe communication restrictions, team formation for the purpose of information sharing among agents leads to an additional 25% improvement in system utility. Finally, we show that agents' private utilities and team sizes can be manipulated to form the best compromise between how "aligned" an agent's utility is with the system utility and how easily an agent can learn that utility.

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Communication for Goal Directed Agents

Cited by 18 publications

References 5 publications

Interest-Based Negotiation as an Extension of Monotonic Bargaining in 3APL

Interest-Based Negotiation as an Extension of Monotonic Bargaining in 3APL

Implementing commitment-based interactions

Handling Communication Restrictions and Team Formation in Congestion Games

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