Distributed fuzzy logic price negotiation in market based multi-agent control

Market-based models in Multi-Agent systems that use fuzzy logic are not new ideas, but most solutions focus on learning and optimization without regards to the resilience of the system. In this paper we present two agent fuzzy inference systems that enable producer and consumer agents in the market to negotiate on the price of the desired resource until a unique allocation is achieved. By constraining consumers to a budget and providing redundant producers capable of meeting market demand under stress conditions, fuzzy price negotiation allows consumer agents to reason alternative solutions should a producing agent fail in the market.

[1]  Arne Andersson,et al.  MARKET‐BASED APPROACHES TO OPTIMIZATION , 2007, Comput. Intell..

[2]  Stathes Hadjiefthymiades,et al.  A Fuzzy Logic System for Bargaining in Information Markets , 2012, TIST.

[3]  C.H. Yong,et al.  Multi-Agent Negotiation System Using Adaptive Fuzzy Logic in Resource Allocation , 2006, The 2nd International Conference on Distributed Frameworks for Multimedia Applications.

[4]  F. Gomide,et al.  Market-based multiagent fuzzy control , 2008, NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society.

[5]  Ai-Min Wang,et al.  Markup pricing strategies between a dominant retailer and competitive manufacturers , 2013, Comput. Ind. Eng..

[6]  T. Ross Fuzzy Logic with Engineering Applications , 1994 .

[7]  Susana Muñoz-Hernández,et al.  A Fuzzy Approach to Resource Aware Automatic Parallelization , 2010, IJCCI.