Papers › Winner Takes It All: Training Performant RL Populations for Combinatorial Optimization

Winner Takes It All: Training Performant RL Populations for Combinatorial Optimization

7 Oct 2022NeurIPS 2023 11arXiv:2210.03475archive 2025-07-28

Nathan Grinsztajn, Daniel Furelos-Blanco, Shikha Surana, Clément Bonnet, Thomas D. Barrett

Applying reinforcement learning (RL) to combinatorial optimization problems is attractive as it removes the need for expert knowledge or pre-solved instances. However, it is unrealistic to expect an agent to solve these (often NP-)hard problems in a single shot at inference due to their inherent complexity. Thus, leading approaches often implement additional search strategies, from stochastic sampling and beam search to explicit fine-tuning. In this paper, we argue for the benefits of learning a population of complementary policies, which can be simultaneously rolled out at inference. To this end, we introduce Poppy, a simple training procedure for populations. Instead of relying on a predefined or hand-crafted notion of diversity, Poppy induces an unsupervised specialization targeted solely at maximizing the performance of the population. We show that Poppy produces a set of complementary policies, and obtains state-of-the-art RL results on four popular NP-hard problems: traveling salesman, capacitated vehicle routing, 0-1 knapsack, and job-shop scheduling.

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get_acting_keys instadeepai/poppy/poppy/utils/data.py community (archive-listed) ran Apache-2.0 (permissive) · 996e62c4cd6ed060 · report
get_agent_contributions instadeepai/poppy/poppy/utils/metrics.py community (archive-listed) ran Apache-2.0 (permissive) · 68f8056fb0caa770 · report
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get_pop_performance_with_random_agents instadeepai/poppy/poppy/utils/metrics.py community (archive-listed) ran Apache-2.0 (permissive) · fb96068e6f59c9ac · report
get_start_positions instadeepai/poppy/poppy/utils/data.py community (archive-listed) ran Apache-2.0 (permissive) · 883057f04316e98e · report
get_metrics instadeepai/poppy/poppy/utils/metrics.py community (archive-listed) unverified Apache-2.0 (permissive) · 05089f65276ed271 · report
get_params instadeepai/poppy/poppy/trainers/validation.py community (archive-listed) unverified Apache-2.0 (permissive) · a5bda23e4f88eecf · report
load_checkpoint instadeepai/poppy/poppy/utils/checkpoint.py community (archive-listed) unverified Apache-2.0 (permissive) · 5720de557f409693 · report

Tasks

AllCombinatorial OptimizationDiversityJob Shop SchedulingReinforcement Learning (RL)Scheduling

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