This book offers a mathematical model of meaning, and thereby provides answers to the following kinds of questions: What is meaning? What is the relation between meaning, information, value, and purpose? What ingredients are necessary for a system to exhibit meaning? What behaviors, and capacities for behavior, are particular to meaning-oriented agents? Is there a relatively simple mathematical model that can adequately capture the dynamics—and diversity—of meaning-oriented agents? How do we best bridge the divide between interpretive paradigms that are qualitative and context-rich and formal methods that are quantitative and domain general?
At the center of this model is a distributed agent that can sense and instigate relatively immediate events and, through these, project and effect relatively mediate events, in reference to a dynamic set of commitments and values (understood as an interpretive ground), and by means of a double integration over past and future worlds.
This book argues that interpretive grounds are central to meaningful processes. It argues that such grounds can be embedded in environments no less than enminded in organisms, and hence turn on relatively objective patterns and resources no less than relatively subjective commitments and values. And it shows that such grounds function as dynamic variables: at once shaped by meaningful processes and shaping of meaningful processes. As will be seen, such a dynamic coupling between figures and grounds, qua interactional practices and interpretive resources, makes this mathematical model of meaning particularly rich and revealing.
In offering such an analysis, this book brings together the objects of signs and the ends of agents, and hence motivation as much as meaning. It connects agents that can select (insofar as they can choose different courses of action in real time) and agents that are selected (such that they can evolve over generational time). It accounts for the behavior of agents that are oriented to diverse kinds of value: from expected utility to free energy, from biological fitness to social status. It shows the connection between the possible worlds of formal semantics and the microstates of statistical physics. And it puts the fixed points of dynamic systems theory into relation with the hermeneutic circles of critical social theory.
While the model incorporates core ideas from a pragmatist tradition, it weaves together a range of powerful ideas from other paradigms, including Bayesian inference, statistical mechanics, decision theory, mathematical biology, evolutionary game theory, possible world semantics, machine learning, linguistics, and anthropology. Its analytic framework thereby provides a relatively seamless integration of distinct methods and theories.
After introducing the model, and reviewing its core assumptions, chapters 2 through 9 explore the entailments of the model, and assess its merits, by using it to analyze a variety of increasingly complex scenarios. As will be seen, the math is done in a complete, but conversational way. And the formalism begins simply and ramps up slowly, such that a wide range of readers will be able to understand the concepts, follow the arguments, imagine novel scenarios, and extend the analysis themselves.