From Word Models to World Models: Translating from Natural Language to the Probabilistic Language of Thought

How does language inform our downstream thinking? In particular, how do humans make meaning from language -- and how can we leverage a theory of linguistic meaning to build machines that think in more human-like ways? In this paper, we propose \textit{rational meaning construction}, a computational framework for language-informed thinking that combines neural models of language with probabilistic models for rational inference. We frame linguistic meaning as a context-sensitive mapping from natural language into a \textit{probabilistic language of thought} (PLoT) -- a general-purpose symbolic substrate for probabilistic, generative world modeling. Our architecture integrates two powerful computational tools that have not previously come together: we model thinking with \textit{probabilistic programs}, an expressive representation for flexible commonsense reasoning; and we model meaning construction with \textit{large language models} (LLMs), which support broad-coverage translation from natural language utterances to code expressions in a probabilistic programming language. We illustrate our framework in action through examples covering four core domains from cognitive science: probabilistic reasoning, logical and relational reasoning, visual and physical reasoning, and social reasoning about agents and their plans. In each, we show that LLMs can generate context-sensitive translations that capture pragmatically-appropriate linguistic meanings, while Bayesian inference with the generated programs supports coherent and robust commonsense reasoning. We extend our framework to integrate cognitively-motivated symbolic modules to provide a unified commonsense thinking interface from language. Finally, we explore how language can drive the construction of world models themselves

From Discursive Practice to Logic? Remarks on Logical Expressivism

This paper proposes a novel account of the conditional locution as grounded in practices of goal- directed cooperative dialogue. It is argued that a conditional semantics can be obtained within a language fragment that lacks this locution, but supports assertive, inferential and directive prac- tices. We take Brandom’s logical expressivist programme as a point of departure, but argue that this programme is empirically flawed as it underestimates the pervasive context-dependence of linguistic items including logical vocabulary. We further take issue with his claim that a discursive practice involving only assertion and inference is sufficient for the conservative introduction and deployment of conditional vocabulary. A more promising route is provided by the introduction of directives, as in so-called “pseudo-imperatives” such as Get individuals to invest their time and the funding will follow: this has a conditional sense that if individuals invest their time, then funding will follow. We propose a semantic analysis for these forms which builds on Kukla and Lance’s account of prescriptives, and argue that our analysis more faithfully captures the “irrealis” nature of conditionals. The analysis is presented in terms of an information-state based dialogue model, with the information state comprising a partitioned commitment store. It is argued that our “dialogical” analysis of conditional reasoning is faithful to Brandom’s Sellarsian intuition of linguistic practice as a game of giving and asking for reasons. We conclude by contextualising and situating Brandom’s programme against the larger field of practice theory, by means of a comparison with the works of sociologist, anthropologist and philosopher Pierre Bourdieu, and suggest that this com- parison reveals further challenges to the expressivist programme. We also take note of Narasimhan et al’s recent proposals for agent-based modelling of social practice theory as a possible basis for future development

Conversation and behavior games in the pragmatics of dialogue

In this article we present the bases for a computational theory of the cognitive processes underlying human communication. The core of the article is devoted to the analysis of the phases in which the process of comprehension of a communicative act can be logically divided: (1) literal meaning, where the reconstruction of the mental states literally expressed by the actor takes place; (2) speaker’s meaning. where the partner reconstructs the communicative intentions of the actor; (3) communicative effect, where the partner possibly modifies his own beliefs and intentions; (4) reaction, where the intentions for the generation of the response are produced: and (5) response, where an overt response is constructed. The model appears to be compatible with relevant facts about human behavior. Our hypothesis is that, through communication, on actor tries to exploit the motivational structures of a partner so that the desired goal is generated. A second point is that social behavior requires that cooperation be maintained at some level. In the case of communication, cooperation is, in general, pursued even when the partner does not adhere to the actor’s goals, and therefore no cooperation occurs at the behavioral level. This important distinction is reflected in the two kinds of games we introduce to account for communication. The main concept implied in communication is that two agents overtly reach a situation of shared mental states. Our model deols with sharedness through two primitives: shared beliefs and communicative intentions

Discovering order

The polarisation of the experimental and observational traditions in linguistics has tended to obscure the common origins of both in intuitions. In this article I explore one form of observational work - conversation analysis - by examining its perceived limitations and the reasons for its insistence on recorded interactions. Its capacity to capture the temporal production and interpretation of utterances is what makes for its distinctive contribution to linguistics, allowing us to discover order in the organisation of talk that escapes introspection. The analysis of data extracts and the examination of case studies impels us to recognise what the investigation of single utterances and utterance pairs cannot: the importance of sequential placement to the understanding of utterances and the centrality of action in language use. © 2004 Elsevier Ltd. All rights reserved

The speaker's linearization problem [and Discussion]

The process of speaking is traditionally regarded as a mapping of thoughts (intentions, feelings, etc.) onto language. One requirement that this mapping has to meet is that the units of information to be expressed be strictly ordered. The channel of speech largely prohibits the simultaneous expression of multiple propositions: the speaker has a linearization problem - that is, a linear order has to be determined over any knowledge structure to be formulated. This may be relatively simple if the informational structure has itself an intrinsic linear arrangement, as often occurs with event structures, but it requires special procedures if the structure is more complex, as is often the case in two- or three-dimensional spatial patterns. How, for instance, does a speaker proceed in describing his home, or the layout of his town? Two powerful constraints on linearization derive, on the one hand, from 'mutual knowledge' and, on the other, from working memory limitations. Mutual knowledge may play a role in that the listener can be expected to derive different implicatures from different orderings (compare 'she married and became pregnant' with 'she became pregnant and married'). Mutual knowledge determinants of linearization are essentially pragmatic and cultural, and dependent on the content of discourse. Working memory limitations affect linearization in that a speaker's linearization strategy will minimize memory load during the process of formulating. A multidimensional structure is broken up in such a way that the number of 'return addresses' to be kept in memory will be minimized. This is attained by maximizing the connectivity of the discourse, and by backtracking to stored addresses in a first-in-last-out fashion. These memory determinants of linearization are presumably biological, and independent of the domain of discourse. An important question is whether the linearization requirement is enforced by the oral modality of speech or whether it is a deeper modality-independent property of language use