Current cognitive science models of perception and action assume that the objects that we move toward and perceive are represented as determinate in our experience of them. A proper phenomenology of perception and action, however, shows that we experience objects indeterminately when we are perceiving them or moving toward them. This indeterminacy, as it relates to simple movement and perception, is captured in the proposed phenomenologically based recurrent network models of brain function. These models provide a possible foundation from which predicative structures may arise as an emergent phenomenon without the positing of a representing subject. These models go some way in addressing the dual constraints of phenomenological accuracy and neurophysiological plausibility that ought to guide all projects devoted to discovering the physical basis of human experience.

Artificial intelligence research has foundered on the issue of representation. When intelligence is approached in an incremental manner, with strict reliance on interfacing to the real world through perception and action, reliance on representation disappears. In this paper we outline our approach to incrementally building complete intelligent Creatures. The fundamental decomposition of the intelligent system is not into independent information processing units which must interface with each other via representations. Instead, the intelligent system is decomposed into independent and parallel activity producers which all interface directly to the world through perception and action, rather than interface to each other particularly much. The notions of central and peripheral systems evaporate – everything is both central and peripheral. Based on these principles we have built a very successful series of mobile robots which operate without supervision as Creatures in standard office environments.

This paper outlines two ideas. The first proposes a basic high-level neuropsychological and neurophenomenological cybernetic framework for discussing the structure of mind and experience. The second is that much, perhaps even most, informational processes in the brain are inherently temporal in nature, i.e. that they are subserved by temporal neural codes. To paraphrase Mari Reiss Jones, in the study of mind and brain, “time is our lost dimension” (Jones 1976). In this view, there is pervasive, common temporal structure in the internal neural representations that subserve both perception and action. This common temporal structure permits perception to facilitate, inform, and even bootstrap action, and vice versa. Time structure in perception, action (movement, behavior), cognition, affect, motivation (drives, goals), and memory may allow these different mental faculties to mutually influence one another.

Merleau-Ponty’s description of Cezanne’s working process reveals two things: first, cognition arises on the basis of perception and action, and, second, cognition arises out of frustration, when an agent confronts non-sense. We briefly present the history of the domain of philosophy and psychology that has claimed that perception-action comes before cognition, especially the work of Merleau-Ponty, Gibson, and Heidegger. We then present an experimental paradigm “front-loading” the Heideggerian phenomenology of encountering tools. The experiments consisted of a dynamical perception-action task and a cognitive task. The results reinforce the distinction between tools being experienced as ready-to-hand and turning into unreadyor present-at-hand when sense-ma kin g was thwarted. A more cognitive attitude towards the task emerged when participants experienced non-sense. We discuss implications of this for the movement sciences.

In this paper I would like to explain, defend, and draw out the implications of this claim. Since the intentional arc is supposed to embody the interconnection of skillful action and perception, I will first lay out an account of skill acquisition that makes explicit what Merleau-Ponty’s claim presupposes. I will then show how his account of skill and the intentional arc it establishes allows Merleau-Ponty to criticize cognitivism and introduce a new account of the relation of perception and action. Finally, I will suggest that neural-network theory supports Merleau-Ponty’s phenomenology, but that it still has a long way to go before it can instantiate an intentional arc.

Existential phenomenologists hold that the two most basic forms of intelligent behavior, learning, and skillful action, can be described and explained without recourse to mind or brain representations. This claim is expressed in two central notions in Merleau-Ponty’s Phenomenology of Perception: the intentional arc and the tendency to achieve a maximal grip. The intentional arc names the tight connection between body and world, such that, as the active body acquires skills, those skills are “stored”, not as representations in the mind, but as dispositions to respond to the solicitations of situations in the world. A phenomenology of skill acquisition confirms that, as one acquires expertise, the acquired know-how is experienced as finer and finer discriminations of situations paired with the appropriate response to each. Maximal grip names the body’s tendency to refine its responses so as to bring the current situation closer to an optimal gestalt. Thus, successful learning and action do not require propositional mental representations. They do not require semantically interpretable brain representations either. Simulated neural networks exhibit crucial structural features of the intentional arc, and Walter Freeman’s account of the brain dynamics underlying perception and action is structurally isomorphic with Merleau-Ponty’s account of the way a skilled agent is led by the situation to move towards obtaining a maximal grip.

Key words: mental representation, successful learning, maximal grip, skillful action, tight connection.

Existential phenomenologists hold that the two most basic forms of intelligent behavior, learning, and skillful action, can be described and explained without recourse to mind or brain representations. This claim is expressed in two central notions in Merleau-Ponty’s Phenomenology of Perception: the intentional arc and the tendency to achieve a maximal grip. The intentional arc names the tight connection between body and world, such that, as the active body acquires skills, those skills are “stored,” not as representations in the mind, but as dispositions to respond to the solicitations of situations in the world. A phenomenology of skill acquisition confirms that, as one acquires expertise, the acquired know-how is experienced as finer and finer discriminations of situations paired with the appropriate response to each. Maximal grip names the body’s tendency to refine its responses so as to bring the current situation closer to an optimal gestalt. Thus, successful learning and action do not require propositional mental representations. They do not require semantically interpretable brain representations either. Simulated neural networks exhibit crucial structural features of the intentional arc, and Walter Freeman’s account of the brain dynamics underlying perception and action is structurally isomorphic with Merleau-Ponty’s account of the way a skilled agent is led by the situation to move towards obtaining a maximal grip.

Key words: Mental representation, successful learning, maximal grip, skillful action, tight connection.

Context: In developing an enactivist phenomenology the analysis of time-consciousness needs to be pushed toward a fully enactivist account. Problem: Varela proposed a neurophenomenology of time-consciousness. I attempt to push this analysis towards a more complete enactivist phenomenology of time-consciousness. Method: I review Varela’s account of time-consciousness, which brings Husserl’s phenomenological analysis of the intrinsic temporal structure of experience into contact with contemporary neuroscience and dynamical systems theory, and pushes it towards a more enactivist conception of consciousness. I argue that Varela’s analysis motivates a closer examination of the phenomenological aspects of the intrinsic temporal structure of experience, understanding it in terms of an action-oriented embodied phenomenology in its most basic manifestation. Results: This fully enactivist phenomenology of time-consciousness continues the analysis initiated by Varela and remains consistent with but also goes beyond Husserl’s later writings on time-consciousness. Implications: This analysis shows that the enactive character of intentionality in general, goes all the way down; it is embedded in the micro-structure of time-consciousness, and this has implications for understanding perception and action. Constructivist content: This account is consistent with Varela’s constructivist approach to cognition.

Key words: Time-consciousness, enactivism, Husserl, Varela.

A novel way to model an agent interacting with an environment is introduced, called an Enactive Markov Decision Process (EMDP). An EMDP keeps perception and action embedded within sensorimotor schemes rather than dissociated, in compliance with theories of embodied cognition. Rather than seeking a goal associated with a reward, as in reinforcement learning, an EMDP agent learns to master the sensorimotor contingencies offered by its coupling with the environment. In doing so, the agent exhibits a form of intrinsic motivation related to the autotelic principle (Steels), and a value system attached to interactions called “interactional motivation.” This modeling approach allows the design of agents capable of autonomous self-programming, which provides rudimentary constitutive autonomy – a property that theoreticians of enaction consider necessary for autonomous sense-making (e.g., Froese & Ziemke). A cognitive architecture is presented that allows the agent to discover, memorize, and exploit spatio-sequential regularities of interaction, called Enactive Cognitive Architecture (ECA). In our experiments, behavioral analysis shows that ECA agents develop active perception and begin to construct their own ontological perspective on the environment. Relevance: This publication relates to constructivism by the fact that the agent learns from input data that does not convey ontological information about the environment. That is, the agent learns by actively experiencing its environment through interaction, as opposed to learning by registering observations directly characterizing the environment. This publication also relates to enactivism by the fact that the agent engages in self-programming through its experience from interacting with the environment, rather than executing pre-programmed behaviors.

According to the predictive coding theory of cognition (PCT), brains are predictive machines that use perception and action to minimize prediction error, i.e. the discrepancy between bottom–up, externally-generated sensory signals and top–down, internally-generated sensory predictions. Many consider PCT to have an explanatory scope that is unparalleled in contemporary cognitive science and see in it a framework that could potentially provide us with a unified account of cognition. It is also commonly assumed that PCT is a representational theory of sorts, in the sense that it postulates that our cognitive contact with the world is mediated by internal representations. However, the exact sense in which PCT is representational remains unclear; neither is it clear that it deserves such status – that is, whether it really invokes structures that are truly and nontrivially representational in nature. In the present article, I argue that the representational pretensions of PCT are completely justified. This is because the theory postulates cognitive structures – namely action-guiding, detachable, structural models that afford representational error detection – that play genuinely representational functions within the cognitive system.

Key words: cartographic maps, generative models, job description challenge, mental representation, predictive coding, structural representation.