CFP: explainable AI for sequential decision-making at XAI-26, Brazil

[Mehrdad Asadi]

Dear all,

We are organizing the second edition of our special session on explainability methods for sequential decision-making agents in Fortaleza, Brazil (XAI World Conference 2026).  

Special Session:

As AI systems increasingly act over time — planning, adapting, making multiple decisions, or collaborating with humans — we can no longer treat them as static “black-box” predictors. This session at XAI-2026 explores how to make sequential, goal-oriented decision-making by AI agents transparent, interpretable and trustworthy.

We welcome work on topics such as: explainable planning, policy or strategy generation; interpretable reinforcement learning, online decision processes or multi-agent systems; explanations of entire sequences or plans (not just individual decisions), summarization or visualization of policy, counterfactuals for plans/policies; human-centered evaluation of sequential decision-making explanations — trust, usability, transparency in long-running or interactive agent settings.

Topics:

• - Explainable planning
• - Explainable online search
• - Interpretable Reinforcement Learning (RL) methods
• - Explainable multi-agent policies/behavior
• - Explainable multi-objective RL
• - Evaluation methods and metrics for policy-level and trajectory-level interpretability
• - Explainability via policy or plan summarisation
• - Learning and reasoning over contrastive plans or policies
• - Advanced frameworks for understanding temporal, multi-step, and cumulative decisions.
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Submission deadline: 1 February 2026

Organizing Committee:

More info: https://xaiworldconference.com/2026/

We look forward to receiving your submissions,