Signaling Friends and Head-Faking Enemies Simultaneously: Balancing Goal Obfuscation and Goal Legibility
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Abstract (arXiv)
In order to be useful in the real world, AI agents need to plan and act in the presence of others, who may include adversarial and cooperative entities. In this paper, we consider the problem where an autonomous agent needs to act in a manner that clarifies its objectives to cooperative entities while preventing adversarial entities from inferring those objectives. We show that this problem is solvable when cooperative entities and adversarial entities use different types of sensors and/or prior knowledge. We develop two new solution approaches for computing such plans. One approach provides an optimal solution to the problem by using an IP solver to provide maximum obfuscation for adversarial entities while providing maximum legibility for cooperative entities in the environment, whereas the other approach provides a satisficing solution using heuristic-guided forward search to achieve preset levels of obfuscation and legibility for adversarial and cooperative entities respectively. We show the feasibility and utility of our algorithms through extensive empirical evaluation on problems derived from planning benchmarks.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 25 May 2019.
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Citing papers per year: 2021: 2; 2022: 2; 2023: 1; 2024: 2; 2025: 1; 2026: 1.
9 papers.
- 2024Theory of Mind abilities of Large Language Models in Human-Robot Interaction : An Illusion?cited by 22
- 2021Human-AI Symbiosis: A Survey of Current Approachescited by 8
- 2021A Unifying Bayesian Formulation of Measures of Interpretability in Human-AIcited by 5
- 2022A Mental-Model Centric Landscape of Human-AI Symbiosiscited by 3
- 2023Planning for Attacker Entrapment in Adversarial Settingscited by 1
- 2022On Almost-Sure Intention Deception Planning that Exploits Imperfect Observerscited by 0
- 2024Explainable Human-AI Interaction: A Planning Perspectivecited by 0
- 2025Optimal sensor deception in stochastic environments with partial observability to mislead a robot to a decoy goalcited by 0
- 2026Probabilistic Plan Legibility with Off-the-shelf Plannerscited by 0
- 2026Probabilistic Plan Legibility with Off-the-shelf Planners4 Sep 2026
- 2025Optimal sensor deception in stochastic environments with partial observability to mislead a robot to a decoy goal7 Mar 2025
- 2024Explainable Human-AI Interaction: A Planning Perspective19 May 2024
- 2024Theory of Mind abilities of Large Language Models in Human-Robot Interaction : An Illusion?10 Jan 2024
- 2023Planning for Attacker Entrapment in Adversarial Settings1 Mar 2023
- 2022On Almost-Sure Intention Deception Planning that Exploits Imperfect Observers1 Sep 2022
- 2022A Mental-Model Centric Landscape of Human-AI Symbiosis18 Feb 2022
- 2021A Unifying Bayesian Formulation of Measures of Interpretability in Human-AI21 Apr 2021
- 2021Human-AI Symbiosis: A Survey of Current Approaches18 Mar 2021