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We study best-effort strategies (aka plans) in fully observablenondeterministic domains (FOND) for goals expressed in Linear Temporal Logic onFinite Traces (LTLf). The notion of best-effort strategy has been introduced toalso deal with the scenario when no agent strategy exists that fulfills thegoal against every possible nondeterministic environment reaction. Suchstrategies fulfill the goal if possible, and do their best to do so otherwise.We present a game-theoretic technique for synthesizing best-effort strategiesthat exploit the specificity of nondeterministic planning domains. We formallyshow its correctness and demonstrate its effectiveness experimentally,exhibiting a much greater scalability with respect to a direct best-effortsynthesis approach based on re-expressing the planning domain as genericenvironment specifications.

LTLf Best-Effort Synthesis in Nondeterministic Planning Domains