Solving sequential games with Boltzmann-learned tactics

Abstract

A new approach is proposed to study strictly sequential problems viz. to substitute time sequences by ensembles of states, to be attained and viewed in parallel. 2-player board games are candidate problems for parallelization. Typical sequences of interest are game tactics to be learned. The latter are observable in the final board — the parallel view — of that sequence. We introduce parallel games, played in steps of m simultaneous moves. Non-deterministic relaxation rules are formulated, with Boltzmann factors, to resolve potential conflicts. An alternative way is simulated annealing to a sequence final board, as boards resemble spin systems. The approach enables a variety of novel game experiments. Sample results for specific tactics are discussed for parallel tic-tac-toe and othello.