The Problem of Mental Action

In mental action there is no motor output to be controlled and no sensory input vector that could be manipulated by bodily movement. It is therefore unclear whether this specific target phenomenon can be accommodated under the predictive processing framework at all, or if the concept of “active inference” can be adapted to this highly relevant explanatory domain. This contribution puts the phenomenon of mental action into explicit focus by introducing a set of novel conceptual instruments and developing a first positive model, concentrating on epistemic mental actions and epistemic self-control. Action initiation is a functionally adequate form of self-deception; mental actions are a specific form of predictive control of effective connectivity, accompanied and possibly even functionally mediated by a conscious “epistemic agent model”. The overall process is aimed at increasing the epistemic value of pre-existing states in the conscious self-model, without causally looping through sensory sheets or using the non-neural body as an instrument for active inference

Emergent intentionality in perception-action subsumption hierarchies

A cognitively-autonomous artificial agent may be defined as one able to modify both its external world-model and the framework by which it represents the world, requiring two simultaneous optimization objectives. This presents deep epistemological issues centered on the question of how a framework for representation (as opposed to the entities it represents) may be objectively validated. In this summary paper, formalizing previous work in this field, it is argued that subsumptive perception-action learning has the capacity to resolve these issues by {\em a)} building the perceptual hierarchy from the bottom up so as to ground all proposed representations and {\em b)} maintaining a bijective coupling between proposed percepts and projected action possibilities to ensure empirical falsifiability of these grounded representations. In doing so, we will show that such subsumptive perception-action learners intrinsically incorporate a model for how intentionality emerges from randomized exploratory activity in the form of 'motor babbling'. Moreover, such a model of intentionality also naturally translates into a model for human-computer interfacing that makes minimal assumptions as to cognitive states

A Subsumption Agent for Collaborative Free Improvisation

This paper discusses the design and evaluation of an artificial agent for collaborative musical free improvisation. The agent provides a means to investigate the underpinnings of improvisational interaction. In connection with this general goal, the system is also used here to explore the implementation of a collaborative musical agent using a specific robotics architecture, Subsumption. The architecture of the system is explained, and its evaluation in an empirical study with expert improvisors is discussed. A follow-up study using a second iteration of the system is also presented. The system design and connected studies bring together Subsumption robotics, ecological psychology, and musical improvisation, and contribute to an empirical grounding of an ecological theory of improvisation

Toward Intelligent Support of Authoring Machinima Media Content: Story and Visualization

The Internet and the availability of authoring tools have enabled a greater community of media content creators, including nonexperts. However, while media authoring tools often make it technically feasible to generate, edit and share digital media artifacts, they do not guarantee that the works will be valuable or meaningful to the community at large. Therefore intelligent tools that support the authoring and creative processes are especially valuable. In this paper, we describe two intelligent support tools for the authoring and production of machinima. Machinima is a technique for producing computer-animated movies through the manipulation of computer game technologies. The first system we describe, ReQUEST, is an intelligent support tool for the authoring of plots. The second system, Cambot, produces machinima from a pre-authored script by manipulating virtual avatars and a virtual camera in a 3D graphical environment

Synchronous Online Philosophy Courses: An Experiment in Progress

There are two main ways to teach a course online: synchronously or asynchronously. In an asynchronous course, students can log on at their convenience and do the course work. In a synchronous course, there is a requirement that all students be online at specific times, to allow for a shared course environment. In this article, the author discusses the strengths and weaknesses of synchronous online learning for the teaching of undergraduate philosophy courses. The author discusses specific strategies and technologies he uses in the teaching of online philosophy courses. In particular, the author discusses how he uses videoconferencing to create a classroom-like environment in an online class

Cortical Software Re-Use: A Computational Principle for Cognitive Development in Robots

The goal of this paper is to propose a candidate for consideration as a computational principle for cognitive development in autonomous robots. The candidate in question is the theory of Cortical Software Re-Use (CSRU) and we will make the case in this paper that it provides a mechanism for the incremental construction of cognitive and language systems from simpler sensory-motor components