Belief Revision


The "Your Actual Belief" Edition

Slate

Next week we're going to discuss the very controversial awards season contender, Nate Parker's The Birth of a Nation. Are you planning to see it in theaters? Record and send us a voice memo at slaterepresent@gmail.com or leave us a message at 646-580-1748 and your thoughts might get shared on next week's episode.


Linford Christie supports view that having sex before sport CAN boost your performance

Daily Mail

While the handful of studies provided some clues about the real effects of sex on sporting performance, Dr Stefani and her colleagues were disappointed with the research on the subject to date. 'In fact, unless it takes place less than two hours before, the evidence actually suggests sexual activity may have a beneficial effect on sports performance.' She added: 'No particular importance has been laid on the psychological or physical effects of sexual activity on sports performance, or upon the different kinds of sports.' She said the review demonstrates the need for proper scientific investigation into the impact of sexual activity on sport performance, clarifying any ethical, gender and sport differences.


A Truth Maintenance System

Classics (Collection 2)

This monotonicity leads to three closely related problems involving commonsense reasoning, the frame problem, and control. For example, when the current set of beliefs is inconsistent, one uses rules like "Reject the smallest set of beliefs possible to restore consistency" and "Reject those beliefs which represent the simplest explanation of the inconsistency." Whatever purposes the reasoner may have, such as solving problems, finding answers, or taking action, it operates by constructing reasons for believing things, desiring things, intending things, or doing or willing things. The current set of beliefs and desires arises from the current set of reasons for beliefs and desires, reasons phrased in terms of other beliefs and desires.


A Truth Maintenance System

Classics (Collection 2)

This monotonicity leads to three closely related problems involving commonsense reasoning, the frame problem, and control. For example, when the current set of beliefs is inconsistent, one uses rules like "Reject the smallest set of beliefs possible to restore consistency" and "Reject those beliefs which represent the simplest explanation of the inconsistency." Whatever purposes the reasoner may have, such as solving problems, finding answers, or taking action, it operates by constructing reasons for believing things, desiring things, intending things, or doing or willing things. The current set of beliefs and desires arises from the current set of reasons for beliefs and desires, reasons phrased in terms of other beliefs and desires.


A first-order formalisation of knowledge and action and action for a multi-agent planning system

Classics (Collection 2)

We take a syntactic approach here: an agent's beliefs are identified with formulas in a first-order language, called the object language (OL). An agent's reasoning process can be modelled as an inference procedure in the OL: from a base set of facts and rules about the world, he drives a full set of beliefs, called his theory of the world. Finally, our work differs from McCarthy's in its careful axiomatization of the relation between ML and OL, and incorporates solutions to several technical problems, including reasoning about belief-nesting (beliefs about beliefs; Creary (Creary 1979) has also described a solution, and a cleaner approach to representing quantified OL expressions in the ML. An alternative to the syntactic approach to representing propositional attitudes is the possible-world approach, so called because it utilizes Kripke-type possible-world semantics for a modal logic of knowledge and belief.


A first-order formalisation of knowledge and action and action for a multi-agent planning system

Classics (Collection 2)

We take a syntactic approach here: an agent's beliefs are identified with formulas in a first-order language, called the object language (OL). An agent's reasoning process can be modelled as an inference procedure in the OL: from a base set of facts and rules about the world, he drives a full set of beliefs, called his theory of the world. Finally, our work differs from McCarthy's in its careful axiomatization of the relation between ML and OL, and incorporates solutions to several technical problems, including reasoning about belief-nesting (beliefs about beliefs; Creary (Creary 1979) has also described a solution, and a cleaner approach to representing quantified OL expressions in the ML. An alternative to the syntactic approach to representing propositional attitudes is the possible-world approach, so called because it utilizes Kripke-type possible-world semantics for a modal logic of knowledge and belief.


Design

Classics (Collection 2)

We arc now ready to walk through the generation of the design of the half adder circuit as shown in Figure 1-1. In Figuie 3-2, we see the results of successive steps along a path through the design space leading to the design of the half adder. The search path shown in Figure 3-2 was the successful path along which a half adder circuit was generated. The steps taken fall into only a few categories: -- Rule Expansions: (steps 1,3,4,6,9, and 11) expansion of a conjunct of the goal list according to some rule in the database.


Design

Classics (Collection 2)

We arc now ready to walk through the generation of the design of the half adder circuit as shown in Figure 1-1. In Figuie 3-2, we see the results of successive steps along a path through the design space leading to the design of the half adder. The search path shown in Figure 3-2 was the successful path along which a half adder circuit was generated. The steps taken fall into only a few categories: -- Rule Expansions: (steps 1,3,4,6,9, and 11) expansion of a conjunct of the goal list according to some rule in the database.


Preferences and Nonmonotonic Reasoning

AI Magazine

Selecting extended logic programming with the answer-set semantics as a "generic" nonmonotonic logic, we show how that logic defines preferred belief sets and how preferred belief sets allow us to represent and interpret normative statements. Conflicts among program rules (more generally, defaults) give rise to alternative preferred belief sets. Finally, we comment on formalisms which explicitly represent preferences on properties of belief sets. Such formalisms either build preference information directly into rules and modify the semantics of the logic appropriately, or specify preferences on belief sets independently of the mechanism to define them.


The 2005 AAAI Classic Paper Awards

AI Magazine

Mitchell and Levesque provide commentary on the two AAAI Classic Paper awards, given at the AAAI-05 conference in Pittsburgh, Pennsylvania. The two winning papers were "Quantifying the Inductive Bias in Concept Learning," by David Haussler, and "Default Reasoning, Nonmonotonic Logics, and the Frame Problem," by Steve Hanks and Drew McDermott.