When AI systems interact with humans in the loop, they are often called on to provide
explanations for their plans and behavior. Past work on plan explanations primarily involved …

Decision-making is challenging in robotics environments with continuous object-centric
states, continuous actions, long horizons, and sparse feedback. Hierarchical approaches …

Recent work on plan recognition as planning has shown great promise in the use of a
domain theory and general planning algorithms for the plan recognition problem. In this …

Past work on plan explanations primarily involved the AI system explaining the correctness
of its plan and the rationale for its decision in terms of its own model. Such soliloquy is …

The objective of top-k planning is to determine a set of k different plans with lowest cost for a
given planning task. In practice, such a set of best plans can be preferred to a single best …

While cost-optimal planning aims at finding one best quality plan, top-k planning deals with
finding a set of solutions, such that no better quality solution exists outside that set. We …

The need for multiple plans has been established by various planning applications. In some,
solution quality has the predominant role, while in others diversity is the key factor. Most …

Effective and efficient planning in continuous state and action spaces is fundamentally hard,
even when the transition model is deterministic and known. One way to alleviate this …

Scenario planning is a commonly used method by companies to develop their long-term
plans. Scenario planning for risk management puts an added emphasis on identifying and …

ABSTRACT Proactive Decision Support aims at improving the decision making experience
of human decision-makers by enhancing the quality of the decisions and the ease of making …