Many Hands Make Light Work: Further Studies in Group Evolution

When niching or speciation is required to perform a task that has several different component parts, standard genetic algorithms (GAs) struggle. They tend to evaluate and select all individuals on the same part of the task, which leads to genetic convergence within the population. The goal of evolutionary niching methods is to enforce diversity in the population so that this genetic convergence is avoided. One drawback with some of these niching methods is that they require a priori knowledge or assumptions about the specific fitness landscape in order to work; another is that many such methods are not set up to work on cooperative tasks where fitness is only relevant at the group level. Here we address these problems by presenting the group GA, described earlier by the authors, which is a group-based evolutionary algorithm that can lead to emergent niching. After demonstrating the group GA on an immune system matching task, we extend the previous work and present two modified versions where the number of niches does not need to be specified ahead of time. In the random-group-size GA, the number of niches is varied randomly during evolution, and in the evolved-group-size GA the number of niches is optimized by evolution. This provides a framework in which we can evolve groups of individuals to collectively perform tasks with minimal a priori knowledge of how many subtasks there are or how they should be shared out.

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Árvore Binomial Construída via Mapas Randômicos para Análise de Ativos Financeiros

Brazilian Review of Finance ◽

10.12660/rbfin.v8n1.2010.1408 ◽

2010 ◽

Vol 8 (1) ◽

pp. 25

Author(s):

Antonio Airton Carneiro De Freitas ◽

José Roberto Securato

Keyword(s):

A Priori ◽

A Priori Knowledge ◽

Financial Assets ◽

Options Market ◽

Binomial Tree ◽

Random Maps ◽

Stationary Probability Density Function ◽

Set Up ◽

Priori Knowledge

Random maps can be constructed from a priori knowledge of the financial assets. It is also addressed the reverse problem, i.e. from a function of an empirical stationary probability density function we set up a random map that naturally leads to an implied binomial tree, allowing the adjustment of models, including the ability to incorporate jumps. An applica- tion related to the options market is presented. It is emphasized that the quality of the model to incorporate a priori knowledge of the financial asset may be affected, for example, by the skewed vision of the analyst. (Full article available in Portuguese only)

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Seeing, Knowing, and Doing

10.1093/oso/9780197503508.001.0001 ◽

2020 ◽

Author(s):

Robert Audi

Keyword(s):

Practical Reasoning ◽

Practical Knowledge ◽

A Priori ◽

Human Action ◽

A Priori Knowledge ◽

Rational Action ◽

Reasons For Action ◽

Discriminative Response ◽

Rich Information ◽

Priori Knowledge

This book provides an overall theory of perception and an account of knowledge and justification concerning the physical, the abstract, and the normative. It has the rigor appropriate for professionals but explains its main points using concrete examples. It accounts for two important aspects of perception on which philosophers have said too little: its relevance to a priori knowledge—traditionally conceived as independent of perception—and its role in human action. Overall, the book provides a full-scale account of perception, presents a theory of the a priori, and explains how perception guides action. It also clarifies the relation between action and practical reasoning; the notion of rational action; and the relation between propositional and practical knowledge. Part One develops a theory of perception as experiential, representational, and causally connected with its objects: as a discriminative response to those objects, embodying phenomenally distinctive elements; and as yielding rich information that underlies human knowledge. Part Two presents a theory of self-evidence and the a priori. The theory is perceptualist in explicating the apprehension of a priori truths by articulating its parallels to perception. The theory unifies empirical and a priori knowledge by clarifying their reliable connections with their objects—connections many have thought impossible for a priori knowledge as about the abstract. Part Three explores how perception guides action; the relation between knowing how and knowing that; the nature of reasons for action; the role of inference in determining action; and the overall conditions for rational action.

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How Reality is Reasonable

10.1093/oso/9780198810384.003.0006 ◽

2018 ◽

Author(s):

Donald C. Williams

Keyword(s):

A Priori ◽

A Priori Knowledge ◽

Dimensional Manifold ◽

The World ◽

Being There ◽

Ways Of Being ◽

Fundamental Entity ◽

Spatiotemporal Relations ◽

Priori Knowledge

This chapter begins with a systematic presentation of the doctrine of actualism. According to actualism, all that exists is actual, determinate, and of one way of being. There are no possible objects, nor is there any indeterminacy in the world. In addition, there are no ways of being. It is proposed that actual entities stand in three fundamental relations: mereological, spatiotemporal, and resemblance relations. These relations govern the fundamental entities. Each fundamental entity stands in parthood relations, spatiotemporal relations, and resemblance relations to other entities. The resulting picture is one that represents the world as a four-dimensional manifold of actual ‘qualitied contents’—upon which all else supervenes. It is then explained how actualism accounts for classes, quantity, number, causation, laws, a priori knowledge, necessity, and induction.

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How Do We Know that We’re Not Brains in Vats?

10.1093/oso/9780199564477.003.0007 ◽

2018 ◽

Author(s):

Keith DeRose

Keyword(s):

Epistemic Justification ◽

A Priori ◽

A Priori Knowledge ◽

Conservative Approach ◽

Contingent Fact ◽

Brains In Vats ◽

Priori Knowledge

In this chapter the contextualist Moorean account of how we know by ordinary standards that we are not brains in vats (BIVs) utilized in Chapter 1 is developed and defended, and the picture of knowledge and justification that emerges is explained. The account (a) is based on a double-safety picture of knowledge; (b) has it that our knowledge that we’re not BIVs is in an important way a priori; and (c) is knowledge that is easily obtained, without any need for fancy philosophical arguments to the effect that we’re not BIVs; and the account is one that (d) utilizes a conservative approach to epistemic justification. Special attention is devoted to defending the claim that we have a priori knowledge of the deeply contingent fact that we’re not BIVs, and to distinguishing this a prioritist account of this knowledge from the kind of “dogmatist” account prominently championed by James Pryor.

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