Abstract This paper presents a methodology based on a variation of the Rapidlyexploring Random Trees (RRTs) that generates feasible trajectories for a team of autonomous aerial veh...
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
The Extended Global Cardinality Constraint (EGCC) is a vital component of constraint solving systems, since it is very widely used to model diverse problems. The literature contai...
We consider the problem of dynamic buying and selling of shares from a collection of N stocks with random price fluctuations. To limit investment risk, we place an upper bound on t...
Abstract—In this paper we consider wireless cooperative multihop networks, where nodes that have decoded the message at the previous hop cooperate in the transmission toward the ...