Conservative Policy Iteration For Zero-Sum POSGs
Occupancy-state reductions make dynamic programming possible for zero-sum partially observable stochastic games (zs-POSGs). Existing point-based solvers usually optimise a central value function. This restores Bellman recursion, but it requires point-based updates over high-dimensional occupancy spaces. We introduce an approximate policy-iteration algorithm for finite-horizon zs-POSGs. The method maintains one policy per player and updates both jointly along occupancy trajectories induced by conservative policy updates. Instead of approximating a full central value function, each update uses a single supporting hyperplane induced by the current joint policy. The algorithm alternates local...
| Authors | Erwan C. Escudie, Matthia Sabatelli, Jilles Steeve Dibangoye |
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| Primary category | cs.AI |
| Published | 27 October 2026 |
| Last updated at source | 27 October 2026 |
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