Although understanding causation is an essential part of nearly every problem domain, it has resisted formal treatment in the languages of logic, probability, and even statistics. Autonomous artificially intelligent agents need to be able to reason about cause and effect. One approach is to provide the agent with formal, computational notions of causality that enable the agent to deduce cause and effect relationships from observations. During the 1990s, formal notions of causality were pursued within the AI community by many researchers, notably by Judea Pearl. Pearl developed the formal language of structural models for reasoning about causation. Among the problems he addressed in this formalism was a problem common to both AI and law, the attribution of causal responsibility or actual causation. Pearl and then Halpern and Pearl developed formal definitions of actual causation in the language of structural models. <p>Within the law, the traditional test for attributing causal responsibility is the counterfactual "but-for" test, which asks whether, but for the defendant's wrongful act, the injury complained of would have occurred. This definition conforms to common intuitions regarding causation in most cases, but gives non-intuitive results in more complex situations where two or more potential causes are present. To handle such situations, Richard Wright defined the NESS Test. Pearl claims that the structural language is an appropriate language to capture the intuitions that motivate the NESS test. While Pearl's structural language is adequate to formalize the NESS test, a recent result of Hopkins and Pearl shows that the Halpern and Pearl definition fails to do so, and this thesis develops an alternative structural definition to formalize the NESS test.

Although understanding causation is an essential part of nearly every problem domain, it has resisted formal treatment in the languages of logic, probability, and even statistics. Autonomous artificially intelligent agents need to be able to reason about cause and effect. One approach is to provide the agent with formal, computational notions of causality that enable the agent to deduce cause and effect relationships from observations. During the 1990s, formal notions of causality were pursued within the AI community by many researchers, notably by Judea Pearl. Pearl developed the formal language of structural models for reasoning about causation. Among the problems he addressed in this formalism was a problem common to both AI and law, the attribution of causal responsibility or actual causation. Pearl and then Halpern and Pearl developed formal definitions of actual causation in the language of structural models. <p>Within the law, the traditional test for attributing causal responsibility is the counterfactual "but-for" test, which asks whether, but for the defendant's wrongful act, the injury complained of would have occurred. This definition conforms to common intuitions regarding causation in most cases, but gives non-intuitive results in more complex situations where two or more potential causes are present. To handle such situations, Richard Wright defined the NESS Test. Pearl claims that the structural language is an appropriate language to capture the intuitions that motivate the NESS test. While Pearl's structural language is adequate to formalize the NESS test, a recent result of Hopkins and Pearl shows that the Halpern and Pearl definition fails to do so, and this thesis develops an alternative structural definition to formalize the NESS test.

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This dissertation defends a certain view of the mind/body relation, according to which although there is a sense in which everything is physical, there is also a sense in which mental phenomena are irreducible to physical phenomena. The reason for this irreducibility, according to the position defended in this work, is that the mental has a certain normative character which the physical lacks. The central thesis defended in the first part of the work is the claim, advanced by Donald Davidson among others, that the mental realm is governed by constitutive principles of rationality. I both attempt to explain what this means precisely and provide arguments as to why we should think that it is true. Having defended the thesis, I then turn to show that it entails that certain mental phenomena are normative. If the normative is generally irreducible to the non-normative -- as I argue there is good reason to hold -- it then follows as a special case that the mental phenomena in question are irreducible to any (non-normative) physical phenomena. Is this form of antireductionism scientifically respectable? In the second part of the dissertation I attempt to establish that it is by showing that the view can be reconciled with a physicalistically acceptable account of mental causation. Focusing on the causal exclusion problem advanced by Jaegwon Kim among others, I critically discuss both reductive and certain nonreductive solutions to the problem that have been advanced by various philosophers. I then propose my own nonreductive solution to the problem, and attempt to draw out some of the consequences of this solution both for physicalism and for the nature of normativity. / text

This thesis investigates the argument structure of transitive particle constructions with the adverb bort, meaning ‘away’, ‘off’. On the basis of approximately 2000 authentic instances of the partially schematic structure [subject verb bort object], I have identified a number of constructions at different levels of abstraction. The overall aim of the thesis is to account for the argument structure of the bort-constructions and to provide an overview of the relation between verb meaning and constructional meaning. Based on the empirical investigation, the argument structure of these constructions seems most adequately accounted for by combining lexical and constructional factors. The investigation shows that the argument structure forms a lexical-constructional continuum: some constructions clearly have verb-specific meaning, whereas others have meaning more or less independently of the verb. In between we find constructions exhibiting various degrees of influence over the lexical properties of the verb. Verb meaning is analyzed within a causative semantic framework, and I assume an association between causation and argument structure. The bort-constructions form a causative continuum ranging from direct, physical to indirect, abstract causation. By analyzing the verbs’ semantics in relation to these different causative structures (semantic frames), I demonstrate that the causative continuum and the argument structure continuum are aligned: the more indirect the causation, the more constructionally dependent (less verb-specific) the argument structure.

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