Decision-theoretic refinement planning is a new technique for finding optimal courses of action. The authors sought to determine whether this technique could identify optimal strategies for medical diagnosis and therapy. An existing model of acute deep venous thrombosis of the lower extremities was encoded for analysis by the decision-theoretic refinement planning system (DRIPS). The encoding r...

Planning in partially observable Markov decision processes (POMDPs) remains a challenging topic in the artificial intelligence community, in spite of recent impressive progress in approximation techniques. Previous research has indicated that online planning approaches are promising in handling large-scale POMDP domains efficiently as they make decisions “on demand” instead of proactively for t...

The aim of this report is to research into game development, build the foundations for a solidgame . Game Architecture and Design: A New Edition. This PDF book provide game architecture anddesign a new edition pdf information. To download free game design and artificial intelligencebournemouth you need to register. ExaminationArtificialIntelligence(214030)Oefententam...

'Traditional' urban simulation models have a number of weaknesses that limit their suitability as planning support tools. However, a 'new wave' of models is currently under development in academic circles, and it is beginning to find application in practical contexts. Based around two simulation techniques that have origins in artificial life and artificial intelligence—cellular automata and mu...

We investigate an open issue in refactoring, namely, the ordering of a sequence of refactorings (conflicts and dependencies amongst the refactorings), and propose a novel solution to the problem via the usage of a partial order planner from the field of Artificial Intelligence. We formulate the problem as an AI planning problem and use AI planning algorithms to come up with a suitable plan i.e....

We propose a novel hybrid planning approach for the automated generation of IT change plans. The algorithm addresses an abstraction mismatch between refinement of tasks and reasoning about the lifecycle and state-constraints of domain objects. To the best of our knowledge, it is the first approach to address this abstraction mismatch for IT Change Management and to be based on Artificial Intell...

Decision-theoretic refinement planning is a new technique for finding optimal courses of action. The authors sought to determine whether this technique could identify optimal strategies for medical diagnosis and therapy. An existing model of acute deep venous thrombosis of the lower extremities was encoded for analysis by the decision-theoretic refinement planning system (DRIPS). The encoding r...

Previous research in Artificial Intelligence has identified the possibility of simplifying planning problems via the identification and exploitation of symmetries. We advance the state of the art in algorithms that exploit symmetry in planning problems by generalizing previous approaches, and applying symmetry reductions to state-based planners. We suggest several algorithms for symmetry exploi...

Our research has successfully extended the planningas-satisfiability paradigm to support contingent planning under uncertainty (uncertain initial conditions, probabilistic effects of actions, uncertain state estimation). Stochastic satisfiability (SSAT), ty pe of Boolean satisfiability problem in which some of the variables have probabilities attached to them, forms the basis of this extension....