Peter Harvey

Support-based distributed search: a new approach for multiagent constraint processing

Distributed Constraint Satisfaction Problems provide a natural mechanism for multiagent coordination and agreement. To date, algorithms for Distributed Constraint Satisfaction Problems have tended to mirror existing non-distributed global-search or local-search algorithms. Unfortunately, existing distributed global-search algorithms derive from classical backtracking search methods and require a total ordering over agents for completeness. Distributed variants of local-search algorithms (such as distributed breakout) inherit the incompleteness properties of their predecessors, or depend on the creation of new communication links between agents. This paper presents an algorithm in which a global ordering is not required, while avoiding the problems of existing local-search algorithms.

Reducing redundancy in the hypertree decomposition scheme

Hypertree decomposition is a powerful technique for transforming near-acyclic CSPs into acyclic CSPs. Acyclic CSPs have efficient, polynomial time solving techniques, and so these conversions are of interest to the constraints community. We present here an improvement on the opt-k-decomp algorithm for finding an optimal hypertree decomposition.

Support-based distributed search

Distributed Constraint Satisfaction Problems provide a natural mechanism for multiagent coordination and agreement. To date, algorithms for Distributed Constraint Satisfaction Problems have tended to mirror existing non-distributed global-search or local-search algorithms. Unfortunately, existing distributed global-search algorithms derive from classical backtracking search methods and require a total ordering over agents for completeness. Distributed variants of local-search algorithms (such as distributed breakout) inherit the incompleteness properties of their predecessors, or depend on the creation of new communication links between agents. This paper presents an algorithm in which a global ordering is not required, while avoiding the problems of existing local-search algorithms.

Practical application of support-based distributed search

Algorithms for distributed constraint satisfaction problems have tended to mirror existing non-distributed global-search or local-search algorithms. Unfortunately, existing distributed global-search algorithms derive from classical backtracking search methods and require a total ordering over variables for completeness. Distributed variants of local-search algorithms (such as distributed breakout) inherit the incompleteness properties of their predecessors. A meeting scheduling problem translates to a DisCSP where a global ordering is difficult to maintain and creates undesirable behaviours. We present a practical demonstration of an algorithm in which a global ordering is not required, while avoiding the problems of local-search algorithms

A relaxation of a semiring constraint satisfaction problem using combined semirings

The Semiring Constraint Satisfaction Problem (SCSP) framework is a popular approach for the representation of partial constraint satisfaction problems. In this framework preferences (semiring values) can be associated with tuples of values of the variable domains. Bistarelli et al. [1] define an abstract solution to a SCSP which consists of the best set of solution tuples for the variables in the problem. Sometimes this abstract solution may not be good enough, and in this case we want to change the constraints so that we solve a problem that is slightly different from the original problem but has an acceptable solution. In [2] we propose a relaxation of a SCSP where we define a measure of distance (a semiring value from a second semiring) between the original SCSP and a relaxed SCSP. In this paper we show how the two semirings can be combined into a single semiring. This combined semiring structure will allow us to use existing tools for SCSPs to solve Combined Semiring Relaxations of SCSPs. At this stage our work is preliminary and needs further investigation to develop into a useful algorithm.

Combining credibility in a source sensitive argumentation system

There exist many approaches to agent-based conflict resolution which adopts argumentation as their underlying conflict resolution machinery. In most argumentation systems, the credibility of argument sources plays a minimal role. This paper focuses on combining credibility of sources in a source sensitive argumentation.

Simple support-based distributed search

Distributed Constraint Satisfaction Problems provide a natural mechanism for multiagent coordination and agreement. To date, algorithms for Distributed Constraint Satisfaction Problems have tended to mirror existing non-distributed global-search or local-search algorithms. Unfortunately, existing distributed global-search algorithms derive from classical backtracking search methods and require a total ordering over agents for completeness. Distributed variants of local-search algorithms (such as distributed breakout) inherit the incompleteness properties of their predecessors, or depend on the creation of new communication links between agents. In [5, 4] a new algorithm was presented designed explicitly for distributed environments so that a global ordering is not required, while avoiding the problems of existing local-search algorithms. This paper presents a significant improvement on that algorithm in performance and provability.