Paraconsistent Reasoning in Cops and Robber Game with Uncertain Information: A Simulation-Based Analysis

摘要

We apply a non-classical four-valued logic in the process of reasoning regarding strategies for cops in a modified game of "Cops and Robber" played on a graph. We extend the game by introducing uncertainty in a form of random failures of detecting devices. This is realized by allowing that a robber can be detected in a node only with the given probability P-A. Additionally, with the probability P-F, cops can be given a false-positive, i.e., they are informed that the robber is located at some node, whereas it is located somewhere else. Consequently, non-zero P-F introduces a measurement noise into the system. All the cops have access to information provided by the detectors and can communicate with each other, so they can coordinate the search. By adjusting the number of detectors,P-A, and P-F we can achieve a smooth transition between the two well-known variants of the game: "with fully visible robber" and "with invisible robber". We compare a simple probabilistic strategy for cops with the non-parametric strategy based on reasoning with a four-valued paraconsistent logic. It is shown that this novel approach leads to a good performance, as measured by the required mean catch-time. We conclude that this type of reasoning can be applied in real-world applications where there is no knowledge about the underlying source of errors which is particularly useful in robotics.