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Learning real-time search, which interleaves planning and acting, allows agents to learn from multiple trials and respond quickly. Such algorithms require no prior knowledge of the environment and can be deployed without pre-processing. We introduce Prioritized-LRTA* (P-LRTA*), a learning real-time search algorithm based on Prioritized Sweeping. P-LRTA*(More)
Real-time heuristic search methods are used by situated agents in applications that require the amount of planning per move to be independent of the problem size. Such agents plan only a few actions at a time in a local search space and avoid getting trapped in local minima by improving their heuristic function over time. We extend a wide class of real-time(More)
We explore the task of designing an efficient multi-agent system that is capable of capturing a single moving target, assuming that every agent knows the location of all agents on a fixed known graph. Many existing approaches are subop-timal as they do not coordinate multiple pursuers and are slow as they re-plan each time the target moves, which makes them(More)
Modern computer games demand real-time simultaneous control of multiple agents. Learning real-time search, which interleaves planning and acting, allows agents to both learn from experience and respond quickly. Such algorithms require no prior knowledge of the environment and can be deployed without pre-processing. We introduce Prioritized-LRTA*, an(More)
The cataluminescence (CTL) of benzene and the benzene homologues toluene and xylene on nanosized γ–Al 2 O 3 doped with Eu 2 O 3 (γ–Al 2 O 3 /Eu 2 O 3) was studied and a sensor of determining these gases was designed. The proposed sensor showed high sensitivity and selectivity at an optimal temperature of 432 ºC, a wavelength of 425 nm and a flow rate of 400(More)
Real-time heuristic search methods are used by situated agents in applications that require the amount of planning per move to be independent of the problem size. Such agents plan only a few actions in a local search space and avoid getting trapped in local minima by improving their heuris-tic function over time. We extend a wide class of real-time search(More)
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For moving target search algorithms, we are considering the case of heuristic search where the goal may change during the course of the search. One motivating application lies with navigation of an autonomous police vehicle chasing a villain [5] in a possibly initially unknown environment under real-time constraints. In this scenario, we would like to(More)
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