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Rasmus G. Tollund

2 accepted papers

2026

Dominance Pruning and Heuristics in Optimal Adversarial Non-Deterministic Planning

AAAI 2026technical

In many planning problems there are non-deterministic actions for which the outcome cannot be fully controlled by the planning agent. For critical tasks, we need to find a strategy that achieves the goal within a predictable time-frame and/or cost. Thus, we consider an adversarial planning setting

Cited by 0SourcePDFScholar
2025

What Makes You Special? Contrastive Heuristics Based on Qualified Dominance

IJCAI 2025

In cost-optimal planning, dominance pruning methods discard states during the search that are dominated by others. However, the binary nature of pruning fails to exploit information when we cannot prove that a state is fully dominated. To this end, we introduce qualified dominance, an automatic meth

Cited by 0SourcePDFScholar