WP5 - Deciding and Learning How to Act

WP5 focusses on the fundamental question:

How does an AI agent decide and learn on how to act?

WP5 aims at empowering the agent with the ability of

• deliberating …

• how to act in the world …

• autonomously

WP5 investigates:

• Reasoning and planning for acting

• Learning strategies/plans from data

• Learning models from data, and then do reasoning and planning

• Learning from past experiences and simulations, for refining strategies/plans or models

• Monitoring the actual outcome of actions

• Recognizing possibly unexpected outcomes

• Reasoning, planning and learning how to deal with unexpected outcomes

• ...

Crucially, empowering an AI agent with the ability to self-deliberate its own behavior carries significant risks, and this ability must by balanced with safety

The autonomous behavior must be:

• Guarded by human guided specifications and oversight

• Verifiable and comprehensible in human terms

• Ultimately trustworthy (WP3)

Assessing safety becomes essential in this context

• Formal verification, model checking and automated synthesis fulfilling safety specifications is central to this WP.