Causality in commonsense reasoning about actions

Proceedings of the 18th International Joint Conference on Artificial Intelligence, 2003

We introduce a logical formalism of irreflexivc causal production relations that possesses both a standard monotonic semantics, and a natural nonmonotonic semantics. The formalism is shown to provide a complete characterization for the causal reasoning behind causal theories from [McCain and Turner, 1997]. It is shown also that any causal relation is reducible to its Horn sub-relation with respect to the nonmonotonic semantics. We describe also a general correspondence between causal relations and abductive systems, which shows, in effect, that causal relations allow to express abductive reasoning. The results of the study seem to suggest causal production relations as a viable general framework for nonmonotonic reasoning.

2010

Cognitive science has developed many different theoretical approaches to causality. All of these approaches assume (sometimes implicitly) that we conceptualize causality in terms of cause and effect. It is argued that the elements-the conceptual primitives-of a cause and of an effect have not been identified yet. Thus, this paper sets out to carry out cognitive-linguistic analysis (systematic sentence manipulations) to answer the following two questions: (1) What are the mental elements that make up a cause? And what are the mental elements that make up an effect? It is argued that Talmy's force dynamics-with three revisions-can be used as a basic framework to identify these elements. The causal concepts investigated are: successful causation (CAUSE), failed causation (DESPITE), negative causation (PREVENT), and disengaged potential negative causation (ENABLE). This account of "force-dynamic elementary causality" is then also compared with other variants of force-dynamic theory. It is furthermore demonstrated how forcedynamic elementary causation can be integrated with epistemic and with counterfactual and probabilistic accounts. Finally, it is discussed how these causal elements might manifest in mental spatiotemporal structure.

The British Journal for the Philosophy of Science, 2006

The paper builds on the basically Humean idea that A is a cause of B iff A and B both occur, A precedes B, and A raises the metaphysical or epistemic status of B given the obtaining circumstances. It argues that in pursuit of a theory of deterministic causation this 'status raising' is best explicated not in regularity or counterfactual terms, but in terms of ranking functions. On this basis, it constructs a rigorous theory of deterministic causation that successfully deals with cases of overdetermination and pre-emption. It finally indicates how the account's profound epistemic relativization induced by ranking theory can be undone. 1 Introduction 2 Variables, propositions, time 3 Induction first 4 Causation 5 Redundant causation 6 Objectivization 1 The major cycles have been produced by David Lewis himself. See Lewis ([1973b], [1986], [2000]). Hints to further cycles may be found there. 2 It is first presented in (Spohn [unpublished]). 3 See, e.g. the April issue of the Journal of Philosophy 97 (2000), or the collection by Collins et al. ([2004]). See also the many references therein, mostly referring to papers since 1995.

2018

We explore the relationships between causal rules and counterfactuals, as well as their relative representation capabilities, in the logical framework of the causal calculus. It will be shown that, though counterfactuals are readily definable on the basis of causal rules, the reverse reduction is achievable only up to a certain logical threshold (basic equivalence). As a result, we will argue that counterfactuals cannot distinguish causal theories that justify different claims of actual causation, which could be seen as the main source of the problem of ‘structural equivalents’ in counterfactual approaches to causation. This will lead us to a general conclusion about the primary role of causal rules in representing causation.

2024

The four main concepts of causality are: causation (deterministic causality) and natural spontaneity (non-volitional indeterminism), and volition (free will by human or other souls) and influence (things intuited, perceived or conceived, making will easier or harder, without however annulling its freedom). We use the term ‘causality’ to signify a genus for these four species of cause-effect relations.

Artificial Intelligence, 2004

In this paper we present a new approach to reasoning about actions and causation which is based on a conditional logic. The conditional implication is interpreted as causal implication. This makes it possible to formalize in a uniform way causal dependencies between actions and their immediate and indirect effects. The proposed approach also provides a natural formalization of concurrent actions and of the dependency (and independency) relations between actions. The properties of causality are formalized as axioms of the conditional connectives and a nonmonotonic (abductive) semantics is adopted for dealing with the frame problem.

Causation, natural laws and explanation, 1999

Four general approaches to the metaphysics of causation are current in Australasian philosophy. One is a development of the regularity theory (attributed to Hume) that uses counterfactuals (Lewis, 1973; 1994). A second is based in the relations of universals, which determine laws, which in turn determine causal interactions of particulars (with the possible exception of singular causation, Armstrong, 1983). This broad approach goes back to Plato, and was also held in this century by Russell, who like Plato, but unlike the more recent version of Armstrong (1983), held there were no particulars as such, only universals. A third view, originating with Reichenbach and revived by Salmon (1984), holds that a causal process is one that can be marked. This view relies heavily on ideas about the transfer of information and the relation of information to probability, but it also needs uneliminable counterfactuals. The fourth view was developed recently by Dowe (1992) and Salmon (1994). It holds that a causal process involves the transfer of a non-zero valued conserved quantity. A considerable advantage of this approach over the others is that it requires neither counterfactuals nor abstracta like universals to explain causation. The theory of causation offered here is a development of the mark approach that entails Dowe’s conserved quantity approach. The basic idea is that causation is the transfer of a particular token of a quantity of information from one state of a system to another. Physical causation is a special case in which physical information instances are transferred from one state of a physical system to another. The approach can be interpreted as a Universals approach (depending on ones approach to mathematical objects and qualities), and it sheds some light on the nature of the regularity approach. After motivating and describing this approach, I will sketch how it can be used to ground natural laws and how it relates to the four leading approaches, in particular how each can be conceived as a special case of my approach. Finally, I will show how my approach satisfies the requirements of Humean supervenience. The approach relies on concrete particulars and computational logic alone, and is the second stage of constructing a minimal metaphysics, started in (Collier 1996, The necessity of natural kinds).

ArXiv, 2017

Actual causation is concerned with the question "what caused what?". Consider a transition between two subsequent observations within a system of elements. Even under perfect knowledge of the system, a straightforward answer to this question may not be available. Counterfactual accounts of actual causation based on graphical models, paired with system interventions, have demonstrated initial success in addressing specific problem cases. We present a formal account of actual causation, applicable to discrete dynamical systems of interacting elements, that considers all counterfactual states of a state transition from t-1 to t. Within such a transition, causal links are considered from two complementary points of view: we can ask if any occurrence at time t has an actual cause at t-1, but also if any occurrence at time t-1 has an actual effect at t. We address the problem of identifying such actual causes and actual effects in a principled manner by starting from a set of ba...

Causation can be understood as a computational process once we understand causation in informational terms. I argue that if we see processes as information channels, then causal processes are most readily interpreted as the transfer of information from one state to another. This directly implies that the later state is a computation from the earlier state, given causal laws, which can also be interpreted computationally. This approach unifies the ideas of causation and computation.