In this work we address the problem of arranging meetings for several participants taking into consideration constraints for personal agendas, transportation schedules and accommodation availability. We have implemented a multi-agent system that solves the problem. Building such applications implies to consider two main issues: collecting information from diierent sources on the Internet, and s...

We present a multi-agent approach to constraint satisfaction where feedback and reinforcement are used in order to avoid local optima and, consequently, to improve the overall solution. Our approach, FeReRA, is based on the fact that an agent’s local best performance does not necessarily contribute to the system’s best performance. Thus, agents may be rewarded for improving the system’s perform...

We consider a multi-agent scenario, where the preferences of several agents are modelled via soft constraint problems and need to be aggregated to compute a single ”socially optimal” solution. We study the resistance of various ways to compute such a solution to influence the result, such as those based on the notion of bribery. In doing this, we link the cost of bribing an agent to the effort ...

Different constraint handling techniques have been used with multiobjective evolutionary algorithms (MOEA) to solve constrained multiobjective optimization problems. It is impossible for a single constraint handling technique to outperform all other constraint handling techniques always on every problem irrespective of the exhaustiveness of parameter tuning. To overcome this selection problem, ...

The multi-objective optimization for a multi-product multi-period four-echelon supply chain network consisting of manufacturing plants, distribution centers (DCs) and retailers each with uncertain services and uncertain customer nodes are aimed in this paper. The two objectives are minimization of the total supply chain cost and maximization of the average number of products dispatched to custo...

This paper presents some prefiminary results of our current attempts to develop a hybrid multi-dimensional knowledge representation scheme which can handle both the incompleteness and uncertainty. We have started from the quantitative temporal constraint information, and extended it with possibilistic quantifiers. We have also extended the former towards a multidimensional constraint-based form...

We consider a multi-agent setting with agents exchanging information over possibly time-varying network, aiming at minimising separable objective function subject to constraints. To achieve this we propose novel subgradient averaging algorithm that allows for non-differentiable functions and different constraint sets per agent. Allowing constraints agent simultaneously communication network con...