Sharif Digital Repository

Design and construction of multi-agent systems is a challenging but an intriguing problem. It is because of the intrinsic distribution of the intelligent components. In such environments the interaction and communication between the constituent parts extends the complexity since appropriate coordination methods need to be designated and employed. In this paper a successful experiment in designing and implementing such an environment is presented1. The test bed for this research is the rescue simulation environment. The architecture of the implemented heterogeneous agents takes advantage of various algorithms. These algorithms make the agents act intelligently by themselves albeit they happen... 

AI planning is one of the research fields that has benefited from employing satisfiability checking methods. These methods have been proved to be very effective in finding optimal plans for both classical and temporal planning. It is also known that by using planning-based heuristic information in solving SAT formulae, one can develop SAT-based planners that are competitive with state-of-the-art non-optimal planners in classical planning domains. However, using satisfiability for non-optimal temporal planning has not been investigated so far. The main difficulty in using satisfiability in temporal planning is the representation of time, which is a continuous concept. Previously introduced... 

In this paper, we introduce DiFF, a novel extension of the Fast Forward (FF) planning system. FF is a domain independent planner that employs a forward heuristic search. Its search strategy is an enforced form of hill climbing. In order to move to a more promising state, FF evaluates successor states without any particular order. In this paper, we introduce a new form of the enforced hill climbing, which we call directed enforced hill climbing, to enhance the efficiency of Fast Forward planning. This strategy evaluates successor states in the order recommended by an adaptive heuristic function. Our experimental results in several planning domains show a significant improvement in the...