I propose a framework for an agent to change its probabilistic beliefs when a new piece of propositional information a is observed. Traditionally, belief change occurs by either a revision process or by an update process, depending on whether the agent is informed with a in a static world or, respectively, whether a is a 'signal' from the environment due to an event occurring. Boutilier suggested a unified model of qualitative belief change, which "combines aspects of revision and update, providing a more realistic characterization of belief change." In this paper, I propose a unified model of quantitative belief change, where an agent's beliefs are represented as a probability distribution over possible worlds. As does Boutilier, I take a dynamical systems perspective. The proposed approach is evaluated against several rationality postulated, and some properties of the approach are worked out.
Reference:
Rens, G. 2016. On stochastic belief revision and update and their combination. In: Sixteenth International Workshop on Non-Monotonic Reasoning, 22-24 April 2016, Cape Town, South Africa
Rens, G. (2016). On stochastic belief revision and update and their combination. Association for the Advancement of Artificial Intelligence. http://hdl.handle.net/10204/8713
Rens, G. "On stochastic belief revision and update and their combination." (2016): http://hdl.handle.net/10204/8713
Rens G, On stochastic belief revision and update and their combination; Association for the Advancement of Artificial Intelligence; 2016. http://hdl.handle.net/10204/8713 .
Sixteenth International Workshop on Non-Monotonic Reasoning, 22-24 April 2016, Cape Town, South Africa. Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, please consult the publisher's website