# Explicability? Legibility? Predictability? Transparency? Privacy? Security? The Emerging Landscape of Interpretable Agent Behavior

arXiv: https://arxiv.org/abs/1811.09722 · HTML: https://mlsanity.com/paper/1811.09722/

## Key facts

- Cited by 30 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Nov 2018.

## Built on by (most cited first, 30 of 30)

- [Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directions](https://mlsanity.com/paper/2310.19775/) (2023)
- [Explainable AI for Robot Failures: Generating Explanations that Improve User Assistance in Fault Recovery](https://mlsanity.com/paper/2101.01625/) (2021)
- [Theory of Mind abilities of Large Language Models in Human-Robot Interaction : An Illusion?](https://mlsanity.com/paper/2401.05302/) (2024)
- [Explainable Autonomous Robots: A Survey and Perspective](https://mlsanity.com/paper/2105.02658/) (2021)
- [Deceptive Reinforcement Learning for Privacy-Preserving Planning](https://mlsanity.com/paper/2102.03022/) (2021)
- [Human-AI Symbiosis: A Survey of Current Approaches](https://mlsanity.com/paper/2103.09990/) (2021)
- [Definitions of intent suitable for algorithms](https://mlsanity.com/paper/2106.04235/) (2021)
- [Motion Reasoning for Goal-Based Imitation Learning](https://mlsanity.com/paper/1911.05864/) (2019)
- [A Unifying Bayesian Formulation of Measures of Interpretability in Human-AI](https://mlsanity.com/paper/2104.10743/) (2021)
- [Explaining Preference-driven Schedules: the EXPRES Framework](https://mlsanity.com/paper/2203.08895/) (2022)
- [A Mental-Model Centric Landscape of Human-AI Symbiosis](https://mlsanity.com/paper/2202.09447/) (2022)
- [Policy Regularization for Legible Behavior](https://mlsanity.com/paper/2203.04303/) (2022)
- [Generating Active Explicable Plans in Human-Robot Teaming](https://mlsanity.com/paper/2109.08834/) (2021)
- [Causal Explanations for Sequential Decision Making Under Uncertainty](https://mlsanity.com/paper/2205.15462/) (2022)
- ["Guess what I'm doing": Extending legibility to sequential decision tasks](https://mlsanity.com/paper/2209.09141/) (2022)
- [Planning for Attacker Entrapment in Adversarial Settings](https://mlsanity.com/paper/2303.00822/) (2023)
- [Safe Explicable Planning](https://mlsanity.com/paper/2304.03773/) (2023)
- [On the Transit Obfuscation Problem](https://mlsanity.com/paper/2402.07420/) (2024)
- [Generalising Planning Environment Redesign](https://mlsanity.com/paper/2402.07799/) (2024)
- [How to Exhibit More Predictable Behaviors](https://mlsanity.com/paper/2404.11296/) (2024)
- [A More General Theory of Diagnosis from First Principles](https://mlsanity.com/paper/2309.16180/) (2023)
- [ICRA Roboethics Challenge 2023: Intelligent Disobedience in an Elderly Care Home](https://mlsanity.com/paper/2311.08783/) (2023)
- [Observer-Aware Probabilistic Planning Under Partial Observability](https://mlsanity.com/paper/2502.10568/) (2025)
- [Safe Explicable Policy Search](https://mlsanity.com/paper/2503.07848/) (2025)
- [Preprint: Exploring Inevitable Waypoints for Unsolvability Explanation in Hybrid Planning Problems](https://mlsanity.com/paper/2504.15668/) (2025)
- [Controlling Intent Expressiveness in Robot Motion with Diffusion Models](https://mlsanity.com/paper/2510.12370/) (2025)
- [Informative Communication of Robot Plans](https://mlsanity.com/paper/2511.13226/) (2025)
- [Fix the Mind, Not the Move: Interpretable AI Assistance via Knowledge-Gap Localization](https://mlsanity.com/paper/2606.05602/) (2026)
- [The Mirror Agent Model: a Bayesian Architecture for Interpretable Agent Behavior](https://mlsanity.com/paper/2609.05190/) (2026)
- [Probabilistic Plan Legibility with Off-the-shelf Planners](https://mlsanity.com/paper/2610.00065/) (2026)

## Abstract (arXiv)

There has been significant interest of late in generating behavior of agents that is interpretable to the human (observer) in the loop. However, the work in this area has typically lacked coherence on the topic, with proposed solutions for "explicable", "legible", "predictable" and "transparent" planning with overlapping, and sometimes conflicting, semantics all aimed at some notion of understanding what intentions the observer will ascribe to an agent by observing its behavior. This is also true for the recent works on "security" and "privacy" of plans which are also trying to answer the same question, but from the opposite point of view -- i.e. when the agent is trying to hide instead of revealing its intentions. This paper attempts to provide a workable taxonomy of relevant concepts in this exciting and emerging field of inquiry.