How to Knit Your Own Markov Blanket

Hohwy (Hohwy 2016, Hohwy 2017) argues there is a tension between the free energy principle and leading depictions of mind as embodied, enactive, and extended (so-called ‘EEE1 cognition’). The tension is traced to the importance, in free energy formulations, of a conception of mind and agency that depends upon the presence of a ‘Markov blanket’ demarcating the agent from the surrounding world. In what follows I show that the Markov blanket considerations do not, in fact, lead to the kinds of tension that Hohwy depicts. On the contrary, they actively favour the EEE story. This is because the Markov property, as exemplified in biological agents, picks out neither a unique nor a stationary boundary. It is this multiplicity and mutability– rather than the absence of agent-environment boundaries as such - that EEE cognition celebrates

What Do Complex Adaptive Systems Look Like and What Are the Implications for Innovation Policy?

This paper explores the use of complex adaptive systems theory in development policy analysis using a case study drawn from recent events in Uganda. It documents the changes that took place in the farming system in Soroti district during an outbreak of African cassava mosaic virus disease (ACMVD) and the subsequent decline in cassava production - the main staple food in the area. Resultant adaptation impacts are analysed across cropping, biological, economic and social systems each of which operate as an interlinked sub-system. The policy implications of this story suggest a policy agenda that recognises adaptation capacity as the life blood of complex adaptive systems. Since these types of systems are found in all realms of human activity, it follows that strengthening this capacity is a key developmental priority that requires linking together new configurations of actors and resources to tackle an ever-changing set of contexts.Complex Adaptive Systems, Innovation Policy, Uganda, Cassava, Adaptation Capacity, Smallholder Production, Policy

Word, Niche and Super-Niche: How Language Makes Minds Matter More

How does language (spoken or written) impact thought? One useful way to approach this important but elusive question may be to consider language itself as a cognition-enhancing animal-built structure. To take this perspective is to view language as a kind of self-constructed cognitive niche. These self-constructed cognitive niches play, I suggest, three distinct but deeply interlocking roles in human thought and reason. Working together, these three interlocking routines radically transform the human mind, and mark a genuine discontinuity in the space of animal minds

Happily entangled: prediction, emotion, and the embodied mind

Recent work in cognitive and computational neuroscience depicts the human cortex as a multi-level prediction engine. This ‘predictive processing’ framework shows great promise as a means of both understanding and integrating the core information processing strategies underlying perception, reasoning, and action. But how, if at all, do emotions and sub-cortical contributions fit into this emerging picture? The fit, we shall argue, is both profound and potentially transformative. In the picture we develop, online cognitive function cannot be assigned to either the cortical or the sub-cortical component, but instead emerges from their tight co-ordination. This tight co-ordination involves processes of continuous reciprocal causation that weave together bodily information and ‘top-down’ predictions, generating a unified sense of what’s out there and why it matters. The upshot is a more truly ‘embodied’ vision of the predictive brain in action

The many faces of precision (Replies to commentaries on “Whatever next? Neural prediction, situated agents, and the future of cognitive science”)

An appreciation of the many roles of ‘precision-weighting’ (upping the gain on select populations of prediction error units) opens the door to better accounts of planning and ‘offline simulation’, makes suggestive contact with large bodies of work on embodied and situated cognition, and offers new perspectives on the ‘active brain’. Combined with the complex affordances of language and culture, and operating against the essential backdrop of a variety of more biologically basic ploys and stratagems, the result is a maximally context-sensitive, restless, constantly self-reconfiguring architecture

Predictions, precision, and agentive attention

The use of forward models (mechanisms that predict the future state of a system) is well established in cognitive and computational neuroscience. We compare and contrast two recent, but interestingly divergent, accounts of the place of forward models in the human cognitive architecture. On the Auxiliary Forward Model (AFM) account, forward models are special-purpose prediction mechanisms implemented by additional circuitry distinct from core mechanisms of perception and action. On the Integral Forward Model (IFM) account, forward models lie at the heart of all forms of perception and action. We compare these neighbouring but importantly different visions and consider their implications for the cognitive sciences. We end by asking what kinds of empirical research might offer evidence favouring one or the other of these approaches