Amnon Meisels – A short Bio

Prof. Amnon Meisels has been a  faculty member of the department of Computer Science at Ben-Gurion University for the last 25 years. Served as head of the Computer Science dept.from 2004 to 2006. The main field of research of Amnon Meisels is Distributed Constraints Reasoning and in the last 7 years a major effort has been to investigate models for self-interested agents in Distributed Constrained Search. His book “Distributed Search by Constrained Agents”, was published by Springer Verlag in January 2008.
Since 2002 Prof. Meisels has lead a group of graduate students at BGU that have established algorithmic standards for distributed search on distributed constraints satisfaction problems (DCSPs) and distributed constraints optimization problems (DCOPs). These include the best performing DCR algorithms for DCSPs - AFC & ConcDB - and for DCOPs - AFB & ConcFB
Prof. Meisels has served on the program committees of all major AI conferences that deal with constraints-based reasoning over the last 7 years. Specifically for Constraints Processing (CP conferences); IJCAI; ECAI; and the series of PATAT conferences on Automatic Timetabling, where he has been a member of the steering committee since 2000. In addition he has been part of the organizing committee of the series of workshops on distributed constraints reasoning (DCR series) every year since 2003.

Important research milestones of the DCSP group at BGU that is headed by Prof. Meisels in the last 15 years include

  • Asynchronous forward-checking & Concurrent search - algorithms for DCSPs
  • Asynchronous ordering heuristics for asynchronous DCSP search
  • Concurrent run-time measures for experimental evaluation of DCSP algorithms
  • Privacy preserving search methods for DCSPs
  • Asynchronous Forward-bounding for DCOPs – establishing the phase transition
  • A correct version of the APO algorithm and an extensive performance evaluation of DCOP algorithms
  • Asymmetric DCOPs – representing self-interested Agents in cooperative search
  • Concurrent search for DCOPs
  • Partially cooperative agents - modelling DCOPs and distributed algorithms for solving
  • Manipulating Boolean games through Taxation and environment variables
  • Distributed search for equilibria in Public Goods Games - use of Incentives
  • Distributed search for high social-welfare equilibria in multi-agents games using incentives


Distributed Search by
Constrained Agents
Algorithms, Performance, Communication