Bayes-optimal performance in a discrete space

Sequential Competitive Facility Location Problem in a Discrete Planar Space

In this paper, there are two competitors in a planar market. The first competitor, called, the leader, opens new facilities. After that, the second competitor, the follower, reacts to the leader’s action and opens r new facilities. The leader and the follower have got some facilities in advance in this market. The optimal locations for leader and follower are chosen among predefined candida...

Bayes-optimal reinforcement learning for discrete uncertainty domains

An important subclass of reinforcement learning problems are those that exhibit only discrete uncertainty: the agent’s environment is known to be sampled from a finite set of possible worlds. In contrast to generic reinforcement learning problems, it is possible to efficiently compute the Bayesoptimal policy for many discrete uncertainty RL domains. We demonstrate empirically that the Bayes-opt...

Empirical Bayes Methods for Discrete Event Simulation Performance Measure Estimation

Discrete event simulation (DES) is a widely-used operational research methodology facilitating the analysis of complex real-world systems. Although, generally speaking, simplicity is greatly desirable in DES modelling applications, in many cases the nature of the underlying system results in simulation models which are large in scale, complex, and expensive to run. As such, the careful design a...

Discrete Bayes with R

Bayes-Optimal Chemotaxis

Chemotaxis plays a crucial role in many biological processes, including nervous system development. However, fundamental physical constraints limit the ability of a small sensing device such as a cell or growth cone to detect an external chemical gradient. One of these is the stochastic nature of receptor binding, leading to a constantly fluctuating binding pattern across the cell's array of re...