Freedom, Fiction and Evidential Decision Theory

Sequential Extensions of Causal and Evidential Decision Theory

Moving beyond the dualistic view in AI where agent and environment are separated incurs new challenges for decision making, as calculation of expected utility is no longer straightforward. The non-dualistic decision theory literature is split between causal decision theory and evidential decision theory. We extend these decision algorithms to the sequential setting where the agent alternates be...

Evidential Markov Decision Processes

This paper proposes a new model, the EMDP (Evidential Markov Decision Process). It is a MDP (Markov Decision Process) for belief functions in which rewards are defined for each state transition, like in a classical MDP, whereas the transitions are modeled as in an EMC (Evidential Markov Chain), i.e. they are sets transitions instead of states transitions. The EMDP can fit to more applications t...

Evidential Morphology and Theory of Mind

The perennial fascination with the relationship between language and thought has generated much research across various disciplines. In recent years, commentators have called for closer examination of the connection between language acquisition and conceptual development (Bowerman & Levinson, 2001). Rather than assuming that language development always presupposes cognitive development, several...

An evidential Markov decision making model

The sure thing principle and the law of total probability are basic laws in classic probability theory. A disjunction fallacy leads to the violation of these two classical laws. In this paper, an Evidential Markov (EM) decision making model based on Dempster-Shafer (D-S) evidence theory and Markov modelling is proposed to address this issue and model the real human decision-making process. In a...

Chemical graph theory-Facts and fiction