Planning under uncertainty is a central problem in the study of automated sequential
decision making, and has been addressed by researchers in many different fields, including …

Hierarchies are one of the most common structures used to understand and conceptualise
the world. Within the field of Artificial Intelligence (AI) planning, which deals with the …

Autonomous AI systems need complex computational techniques for planning and
performing actions. Planning and acting require significant deliberation because an …

There have been widespread claims about Large Language Models (LLMs) being able to
successfully verify or self-critique their candidate solutions in reasoning problems in an …

Intelligent agents are employed as the central characters in this new introductory text.
Beginning with elementary reactive agents, Nilsson gradually increases their cognitive …

Planning is the model-based approach to autonomous behavior where the agent behavior is
derived automatically from a model of the actions, sensors, and goals. The main challenges …

We introduce a new approach to planning in STRIPS-like domains based on constructing
and analyzing a compact structure we call a planning graph. We describe a new planner …

Recent years have witnessed the birth of a new paradigm for learning environments:
animated pedagogical agents. These lifelike autonomous characters cohabit learning …

Narrative, and in particular storytelling, is an important part of the human experience.
Consequently, computational systems that can reason about narrative can be more effective …