Mark Jago

Gaining information can be modelled as a narrowing of epistemic space . Intuitively, becoming informed that such-and-such is the case rules out certain scenarios or would-be possibilities. Chalmers’s account of epistemic space treats it as a space of a priori possibility and so has trouble in dealing with the information which we intuitively feel can be gained from logical inference. I propose a more inclusive notion of epistemic space, based on Priest’s notion of open worlds yet which contains only those epistemic scenarios which are not obviously impossible. Whether something is obvious is not always a determinate matter and so the resulting picture is of an epistemic space with fuzzy boundaries.

The logical omniscience problem, whereby standard models of epistemic logic treat an agent as believing all consequences of its beliefs and knowing whatever follows from what else it knows, has received plenty of attention in the literature. But many attempted solutions focus on a fairly narrow specification of the problem: avoiding the closure of belief or knowledge, rather than showing how the proposed logic is of philosophical interest or of use in computer science or artificial intelligence. Sentential epistemic logics, as opposed to traditional possible worlds approaches, do not suffer from the problems of logical omniscience but are often thought to lack interesting epistemic properties. In this paper, I focus on the case of rule-based agents, which play a key role in contemporary AI research but have been neglected in the logical literature. I develop a framework for modelling monotonic, nonmonotonic and introspective rule-based reasoners which have limited cognitive resources and prove that the resulting models have a number of interesting properties. An axiomatization of the resulting logic is given, together with completeness, decidability and complexity results.

We defend the view that an indexical uttered by an actor works on the model of deferred reference. If it defers to a character which does not exist, it is an empty term, just as ‘Hamlet’ and ‘Ophelia’ are. The utterance in which it appears does not express a proposition and thus lacks a truth value. We advocate an ontologically parsimonious, anti-realist, position. We show how the notion of truth in our use and understanding of indexicals (and fictional names) as they appear within a fiction is not a central issue. We claim that our use and understanding of indexicals (and names) rests on the fact that their cognitive contribution is not exhausted by their semantic contribution.

According to truthmaker theory, particular truths are true in virtue of the existence of particular entities. Truthmaker maximalism holds that this is so for all truths. Negative existential and other ‘negative’ truths threaten the position. Despite this, maximalism is an appealing thesis for truthmaker theorists. This motivates interest in parsimonious maximalist theories, which do not posit extra entities for truthmaker duty. Such theories have been offered by David Lewis and Gideon Rosen, Ross Cameron, and Jonathan Schaffer. But these theories cannot be sustained, I’ll argue, and hence maximalism comes with a serious ontological cost. Neither Armstrong’s invocation of totality facts nor the Martin-Kukso line on absences can meet this cost satisfactorily. I’ll claim that negative facts are the best (and perhaps only) way out of the problem for the truthmaker maximalist.

Negative facts get a bad press. One reason for this is that it is not clear what negative facts are. We provide a theory of negative facts on which they are no stranger than positive atomic facts. We show that none of the usual arguments hold water against this account. Negative facts exist in the usual sense of existence and conform to an acceptable Eleatic principle. Furthermore, there are good reasons to want them around, including their roles in causation, chance-making and truth-making, and in constituting holes and edges.

Agents which perform inferences on the basis of unreliable information need an ability to revise their beliefs if they discover an inconsistency. Such a belief revision algorithm ideally should be rational, should respect any preference ordering over the agent’s beliefs (removing less preferred beliefs where possible) and should be fast. However, while standard approaches to rational belief revision for classical reasoners allow preferences to be taken into account, they typically have quite high complexity. In this paper, we consider belief revision for agents which reason in a simpler logic than full first-order logic, namely rule-based reasoners. We show that it is possible to define a contraction operation for rule-based reasoners, which we call McAllester contraction, which satisfies all the basic Alchourrón, Gärdenfors and Makinson (AGM) postulates for contraction (apart from the recovery postulate) and at the same time can be computed in polynomial time. We prove a representation theorem for McAllester contraction with respect to the basic AGM postulates (minus recovery), and two additional postulates. We then show that our contraction operation removes a set of beliefs which is least preferred, with respect to a natural interpretation of preference. Finally, we show how McAllester contraction can be used to define a revision operation which is also polynomial time, and prove a representation theorem for the revision operation.