Designing Ecosystems of Intelligence from First Principles

This white paper lays out a vision of research and development in the field of artificial intelligence for the next decade (and beyond). Its denouement is a cyber-physical ecosystem of natural and synthetic sense-making, in which humans are integral participants -- what we call ''shared intelligence''. This vision is premised on active inference, a formulation of adaptive behavior that can be read as a physics of intelligence, and which inherits from the physics of self-organization. In this context, we understand intelligence as the capacity to accumulate evidence for a generative model of one's sensed world -- also known as self-evidencing. Formally, this corresponds to maximizing (Bayesian) model evidence, via belief updating over several scales: i.e., inference, learning, and model selection. Operationally, this self-evidencing can be realized via (variational) message passing or belief propagation on a factor graph. Crucially, active inference foregrounds an existential imperative of intelligent systems; namely, curiosity or the resolution of uncertainty. This same imperative underwrites belief sharing in ensembles of agents, in which certain aspects (i.e., factors) of each agent's generative world model provide a common ground or frame of reference. Active inference plays a foundational role in this ecology of belief sharing -- leading to a formal account of collective intelligence that rests on shared narratives and goals. We also consider the kinds of communication protocols that must be developed to enable such an ecosystem of intelligences and motivate the development of a shared hyper-spatial modeling language and transaction protocol, as a first -- and key -- step towards such an ecology.Comment: 23+18 pages, one figure, one six page appendi

The Teleological Theory of Representation

Book chapter (revised

The intersection between Descriptivism and Meliorism in reasoning research: further proposals in support of 'soft normativism'

The rationality paradox centres on the observation that people are highly intelligent, yet show evidence of errors and biases in their thinking when measured against normative standards. Elqayam and Evans (e.g., 2011) reject normative standards in the psychological study of thinking, reasoning and deciding in favour of a ‘value-free’ descriptive approach to studying high-level cognition. In reviewing Elqayam and Evans’ position, we defend an alternative to descriptivism in the form of ‘soft normativism’, which allows for normative evaluations alongside the pursuit of descriptive research goals. We propose that normative theories have considerable value provided that researchers: (1) are alert to the philosophical quagmire of strong relativism; (2) are mindful of the biases that can arise from utilising normative benchmarks; and (3) engage in a focused analysis of the processing approach adopted by individual reasoners. We address the controversial ‘is–ought’ inference in this context and appeal to a ‘bridging solution’ to this contested inference that is based on the concept of ‘informal reflective equilibrium’. Furthermore, we draw on Elqayam and Evans’ recognition of a role for normative benchmarks in research programmes that are devised to enhance reasoning performance and we argue that such Meliorist research programmes have a valuable reciprocal relationship with descriptivist accounts of reasoning. In sum, we believe that descriptions of reasoning processes are fundamentally enriched by evaluations of reasoning quality, and argue that if such standards are discarded altogether then our explanations and descriptions of reasoning processes are severely undermined

Social Mental Shaping: Modelling the Impact of Sociality on Autonomous Agents' Mental States

This paper presents a framework that captures how the social nature of agents that are situated in a multi-agent environment impacts upon their individual mental states. Roles and relationships provide an abstraction upon which we develop the notion of social mental shaping. This allows us to extend the standard Belief-Desire-Intention model to account for how common social phenomena (e.g. cooperation, collaborative problem-solving and negotiation) can be integrated into a unified theoretical perspective that reflects a fully explicated model of the autonomous agent's mental state

Student Engagement: The Effects of Goals, Personality, Relations, and Society

Undergraduate Applie

The role of psychological characteristics in facilitating the pathway to elite performance. Part 2: Examining environmental and stage-related differences in skills and behaviors

MacNamara, Button, & Collins (under review) proposed that if individuals are to fulfill their potential they must possess and systematically develop a specific set of skills (termed Psychological Characteristics of Developing Excellence or PCDEs) that allow them to interact effectively with the developmental opportunities they are afforded. Given the complexity of the developmental pathway, it may well be that different skills are needed at different stages of development and across different performance domains. Twenty-four elite participants from team sports, individual sports, and music were purposefully sampled from different domains and interviewed on their experiences of their own pathways to excellence. Results suggested that although PCDEs were important throughout development, the manner by which they were deployed depended on stage, domain, and the characteristics of the individual performer. These findings support proposals to systematically incorporate PCDEs into TID practices because these may be the key feature in maintaining progress toward excellence