Synthesizing Best-effort Strategies under Multiple Environment Specifications

We formally introduce and solve the synthesis problem for LTL goals in the case of multiple, even contradicting, assumptions about the environment. Our solution concept is based on ``best-effort strategies'' which are agent plans that, for each of the environment specifications individually, achieve the agent goal against a maximal set of environments satisfying that specification. By means of a novel automata theoretic characterization we demonstrate that this best-effort synthesis for multiple environments is 2ExpTime-complete, i.e., no harder than plain LTL synthesis. We study an important case in which the environment specifications are increasingly indeterminate, and show that as in the case of a single environment, best-effort strategies always exist for this setting. Moreover, we show that in this setting the set of solutions are exactly the strategies formed as follows: amongst the best-effort agent strategies for ɸ under the environment specification E1, find those that do a best-effort for ɸ under (the more indeterminate) environment specification E2, and amongst those find those that do a best-effort for ɸ under the environment specification E3, etc.

[1]  Alberto Camacho,et al.  Towards a Unified View of AI Planning and Reactive Synthesis , 2019, ICAPS.

[2]  Krzysztof R. Apt,et al.  Lectures in Game Theory for Computer Scientists , 2011 .

[3]  Paola Bonizzoni,et al.  On Automata on Infinite Trees , 1992, Theor. Comput. Sci..

[4]  Bernd Finkbeiner,et al.  Dependency-Based Compositional Synthesis , 2020, ATVA.

[5]  R. Odríguez,et al.  Fully Observable Non-deterministic Planning as Assumption-Based Reactive Synthesis , 2018 .

[6]  Amir Pnueli,et al.  On the synthesis of a reactive module , 1989, POPL '89.

[7]  Fred Kröger,et al.  Temporal Logic of Programs , 1987, EATCS Monographs on Theoretical Computer Science.

[8]  Giuseppe De Giacomo,et al.  Planning under LTL Environment Specifications , 2019, ICAPS.

[9]  Dietmar Berwanger,et al.  Admissibility in Infinite Games , 2007, STACS.

[10]  Aniello Murano,et al.  Probabilistic Strategy Logic , 2019, IJCAI.

[11]  Marco Faella,et al.  Admissible Strategies in Infinite Games over Graphs , 2009, MFCS.

[12]  Sasha Rubin,et al.  Verification of multi-agent systems with public actions against strategy logic , 2020, Artif. Intell..

[13]  Bernd Finkbeiner,et al.  Automatic Compositional Synthesis of Distributed Systems , 2014, FM.

[14]  Bernd Finkbeiner,et al.  Synthesis in Distributed Environments , 2017, FSTTCS.

[15]  Pierre Wolper,et al.  Reasoning About Infinite Computations , 1994, Inf. Comput..

[16]  Aniello Murano,et al.  Reasoning About Strategies: On the Model-Checking Problem , 2011, ArXiv.

[17]  Alberto Camacho,et al.  Finite LTL Synthesis with Environment Assumptions and Quality Measures , 2018, KR.

[18]  Yuxiao Hu,et al.  Generalized Planning: Synthesizing Plans that Work for Multiple Environments , 2011, IJCAI.

[19]  Aniello Murano,et al.  Strategy logic with imperfect information , 2017, 2017 32nd Annual ACM/IEEE Symposium on Logic in Computer Science (LICS).

[20]  Fahiem Bacchus,et al.  Planning for temporally extended goals , 1996, Annals of Mathematics and Artificial Intelligence.

[21]  Jean-François Raskin,et al.  The complexity of admissibility in Omega-regular games , 2013, CSL-LICS.

[22]  Bernd Finkbeiner,et al.  Does It Pay to Extend the Perimeter of a World Model? , 2011, FM.

[23]  David E. Muller,et al.  Simulating Alternating Tree Automata by Nondeterministic Automata: New Results and New Proofs of the Theorems of Rabin, McNaughton and Safra , 1995, Theor. Comput. Sci..

[24]  Giuseppe De Giacomo,et al.  Synthesis under Assumptions , 2018, KR.

[25]  Siddharth Srivastava,et al.  Foundations and applications of generalized planning , 2011, AI Commun..

[26]  Giuseppe De Giacomo,et al.  Best-Effort Synthesis: Doing Your Best Is Not Harder Than Giving Up , 2021, IJCAI.

[27]  Giuseppe De Giacomo,et al.  Automata-Theoretic Foundations of FOND Planning for LTLf and LDLf Goals , 2018, IJCAI.

[28]  Sebastian Sardiña,et al.  Multi-Tier Automated Planning for Adaptive Behavior , 2020, ICAPS.

[29]  Giuseppe De Giacomo,et al.  Synthesizing strategies under expected and exceptional environment behaviors , 2020, IJCAI.

[30]  Giuseppe De Giacomo,et al.  Imperfect-Information Games and Generalized Planning , 2016, IJCAI.