Conditioning and AGM-like belief change in the Desirability-Indifference framework
We show how the AGM framework for belief change (expansion, revision, contraction) can be extended to deal with conditioning in the so-called Desirability-Indifference framework, based on abstract notions of accepting and rejecting options, as well as on abstract notions of events. This level of abstraction allows us to deal simultaneously with classical and quantum probability theory.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Conditioning Accept-Desirability models in the context of AGM-like belief change
We discuss conditionalisation for Accept-Desirability models in an abstract decision-making framework, where uncertain rewards live in a general linear space, and events are special projection operators on that linear sp…
Conditioning through indifference in quantum mechanics
We can learn (more) about the state a quantum system is in through measurements. We look at how to describe the uncertainty about a quantum system's state conditional on executing such measurements. We show that by explo…
'Indifference' methods for managing agent rewards
`Indifference' refers to a class of methods used to control reward based agents. Indifference techniques aim to achieve one or more of three distinct goals: rewards dependent on certain events (without the agent being mo…
Natural revision is contingently-conditionalized revision
Natural revision seems so natural: it changes beliefs as little as possible to incorporate new information. Yet, some counterexamples show it wrong. It is so conservative that it never fully believes. It only believes in…
Select to Perfect: Imitating desired behavior from large multi-agent data
AI agents are commonly trained with large datasets of demonstrations of human behavior. However, not all behaviors are equally safe or desirable. Desired characteristics for an AI agent can be expressed by assigning desi…
AI Agent