In this chapter, we introduce the influential work of H. Paul Grice, focusing on his claims about indirectly communicated meaning. Grice is generally acknowledged as the first person to propose an account of how hearers derive implied meaning. He coined the now widely accepted term implicature to describe any proposition that is communicated without being directly stated, and he offered an account of how hearers derive implicatures by working out what a speaker meant to communicate beyond what has been directly and explicitly stated in an utterance. We begin this chapter by exploring Grice’s distinction between ‘what is said’ and what is implicated. We then move on to discuss his cooperative principle (CP) and its associated maxims. Speakers, it is claimed, abide by certain norms when they take part in a conversation. We outline Grice’s formulation of these norms, and the role they play in inferential processes and implicature derivation. The chapter closes with a discussion of the different categories of implicature that Grice identified. We look at examples to illustrate the role that context plays in inferential processes for each category of implicature.

We continue our discussion of hidden Markov models (HMMs) and consider in this chapter the solution of decoding problems. Specifically, given a sequence of observations $\{y_n,n=1,2,\dots ,N\}$, we would like to devise mechanisms that allow us to estimate the underlying sequence of state or latent variables $\{z_n,n=1,2,\dots ,N\}$. That is, we would like to recover the state evolution that “most likely” explains the measurements. We already know how to perform decoding for the case of mixture models with independent observations by using (38.12a)–(38.12b). The solution is more challenging for HMMs because of the dependency among the states.

Distinguishes between adaptive and maladaptive anxiety. Describes the essential features of, and models and treatments for, panic attacks and panic disorder. Describes the essential features of, and models and treatments for, phobias. Describes the essential features of, and models and treatments for, generalized anxiety disorder. Describes the essential features of, and models and treatments for, obsessive-compulsive and related disorders.

Explains the physiological processes and the medical treatments behind the biological perspective of psychopathology. Defines the psychodynamic perspective and the techniques used in psychodynamic therapy. Describes the behavioral perspective and related techniques. Contrasts the cognitive theories of Beck, Ellis, and the 3rd Wave approaches of ACT and DBT. Describes the sociocultural perspective, and how systems and group therapy utilize this approach. Analyzes how multiperspective approaches to psychopathology integrate various approaches.

Identifies the important characteristics of clinical assessment. Describes the various tests that psychologists use. Explains the way psychologists organize information in an intake report. Explains the purpose and limitations of diagnosis. Summarizes the way diagnostic manuals have changed over time. Describes the research evaluating the effectiveness of psychotherapy.

So far, in these lectures, we have seen how an unfolding denotational text-in-context figurates the identities and interactional textual projects of particular participants, furthering their apparent goals in the interaction. Our analysis of the transcript of Mr. A and Ms. C as well as that of Mr. Black and Ms. Mercer in Lecture 3 demonstrated how deictics (indexical referentials) and social indexicals – as elements of pragmatic paradigms – are centrally involved as they are metricalized into segmentations of phases in discursive space-time. We also saw that these unique communicative events, like all events, are interdiscursively connected in fields of interactions.

The various reinforcement learning algorithms described in the last two chapters rely on estimating state values, ${\upsilon }^{\pi }\left(s\right)$, or state–action values, $q^{\pi }(s,a)$, directly.

The mean-square-error (MSE) problem of estimating a random variable $\mathit{x}$ from observations of another random variable $\mathit{y}$ seeks a mapping $c\left(\mathit{y}\right)$ that solves

In the last lecture, we set the background for being able to talk at all about “linguistic relativity” by reviewing the post-Enlightenment concern with language as the instrument of rationality – grammar and logic in the medieval trivium – as well as by introducing the problem that linguistic diversity poses for it, let alone the diversity of the cast-off third member of the trivium, rhetoric, that is, the socioculturally effective use of language in events of communication. We then developed the necessary strategy of structural or formal linguistics if it is to be an empirical science of language by first considering the phonologico-phonetic categoriality of language. We then expanded this analysis by considering other planes of language, an approach we develop here. Our analysis suggested that “meanings” or “concepts” as projected from formal distributional categorizations.