Learning action-oriented models through active inference

Converging theories suggest that organisms learn and exploit probabilistic models of their environment. However, it remains unclear how such models can be learned in practice. The open-ended complexity of natural environments means that it is generally infeasible for organisms to model their environment comprehensively. Alternatively, action-oriented models attempt to encode a parsimonious representation of adaptive agent-environment interactions. One approach to learning action-oriented models is to learn online in the presence of goal-directed behaviours. This constrains an agent to behaviourally relevant trajectories, reducing the diversity of the data a model need account for. Unfortunately, this approach can cause models to prematurely converge to sub-optimal solutions, through a process we refer to as a bad-bootstrap. Here, we exploit the normative framework of active inference to show that efficient action-oriented models can be learned by balancing goal-oriented and epistemic (information-seeking) behaviours in a principled manner. We illustrate our approach using a simple agent-based model of bacterial chemotaxis. We first demonstrate that learning via goal-directed behaviour indeed constrains models to behaviorally relevant aspects of the environment, but that this approach is prone to sub-optimal convergence. We then demonstrate that epistemic behaviours facilitate the construction of accurate and comprehensive models, but that these models are not tailored to any specific behavioural niche and are therefore less efficient in their use of data. Finally, we show that active inference agents learn models that are parsimonious, tailored to action, and which avoid bad bootstraps and sub-optimal convergence. Critically, our results indicate that models learned through active inference can support adaptive behaviour in spite of, and indeed because of, their departure from veridical representations of the environment. Our approach provides a principled method for learning adaptive models from limited interactions with an environment, highlighting a route to sample efficient learning algorithms

Learning an Unknown Network State in Routing Games

We study learning dynamics induced by myopic travelers who repeatedly play a routing game on a transportation network with an unknown state. The state impacts cost functions of one or more edges of the network. In each stage, travelers choose their routes according to Wardrop equilibrium based on public belief of the state. This belief is broadcast by an information system that observes the edge loads and realized costs on the used edges, and performs a Bayesian update to the prior stage's belief. We show that the sequence of public beliefs and edge load vectors generated by the repeated play converge almost surely. In any rest point, travelers have no incentive to deviate from the chosen routes and accurately learn the true costs on the used edges. However, the costs on edges that are not used may not be accurately learned. Thus, learning can be incomplete in that the edge load vectors at rest point and complete information equilibrium can be different. We present some conditions for complete learning and illustrate situations when such an outcome is not guaranteed

Dynamics Governing Women's Decision on Reproductive Health Matters: Reflections from a Qualitative Study in Central India

One of the major challenges of Reproductive and Child Health Programme in India is addressing the barriers in communication and improve dialogue between diverse stakeholders, particularly women in the community. Through a qualitative study conducted in one of the rural districts of India, it was attempted to understand the factors affecting women's decision-making process. It is observed that most of the factors are affected by strong intrinsic environment and hence it becomes important for programme managers to understand the environment first in order to design an acceptable and effective communication strategy. In this study, knowledge, tradition, stigma and accessibility of services are identified as the key primary factors affecting decision making of women in the community, particularly on their health related issues. These in turn are governed by various supporting factors. Finally, it is observed that communication strategies can achieve their desired objective only when the local intrinsic environment is taken into cognisance

Meaning Management: A Framework for Leadership Ontology

Leadership is a multifaceted and complex subject of research and demands a sound ontological stance that guides studies for the development of more integrative leadership theories. In this paper, I propose the leadership ontology PVA (perception formation – value creation – achievement realization) and associate it with the two existing leadership ontologies: TRIPOD (leader – member – shared goals) and DAC (direction – alignment – commitment). The leadership ontology PVA, based on a new theory called “meaning management,” consists of three circularly supporting functions: cognitive function to form perception, creative function to generate value, and communicative function to realize higher levels of achievement. The PVA is an epistemology-laden ontology since the meaning management theory allows one to make propositions that explicitly link its three functions with the leadership outcomes: perception, value, and achievement. Moreover, the PVA leadership ontology transcends and includes both the conventional TRIPOD ontology and the DAC ontology

the cultural evolution of institutional religions

In recent work, Atran, Henrich, Norenzayan and colleagues developed an account of religion that reconciles insights from the ‘by-product’ accounts and the adaptive accounts. According to their synthesis, the process of cultural group selection driven by group competition has recruited our proclivity to adopt and spread religious beliefs and engage in religious practices to increase within group solidarity, harmony and cooperation. While their account has much merit, I believe it only tells us half the story of how institutional religions have evolved. Their cultural evolutionary account of religion only looks at the cultural dynamics arising from competition between groups, not at the dynamics arising from within the group. Drawing from game-theoretic analyses of the emergence and cultural evolution of social institutions, I outline two sets of important ‘within-group’ dynamics that shape institutional religions. The first follow from the necessity to keep the interaction of the participants in an equilibrium state in order to maintain the social institution. The second arise from the competition of institutional features for traction within the group. Bringing these dynamics into account enables us to explain prominent features of institutional religions that cannot be satisfactorily explained by the current model of the cultural evolution of religions

Behind the price: on the role of agent's reflexivity in financial market microstructure

In this chapter we review some recent results on the dynamics of price formation in financial markets and its relations with the efficient market hypothesis. Specifically, we present the limit order book mechanism for markets and we introduce the concepts of market impact and order flow, presenting their recently discovered empirical properties and discussing some possible interpretation in terms of agent's strategies. Our analysis confirms that quantitative analysis of data is crucial to validate qualitative hypothesis on investors' behavior in the regulated environment of order placement and to connect these micro-structural behaviors to the properties of the collective dynamics of the system as a whole, such for instance market efficiency. Finally we discuss the relation between some of the described properties and the theory of reflexivity proposing that in the process of price formation positive and negative feedback loops between the cognitive and manipulative function of agents are present.Comment: 12 pages, 1 figur

The constitution of risk communication in advanced liberal societies

This article aims to bring to the fore some of the underlying rationales that inform common conceptions of the constitution of risk communication in academic and policy communities. ‘Normative’, ‘instrumental’ and ‘substantive’ imperatives typically employed in the utilisation of risk communication are first outlined. In light of these considerations a theoretical scheme is subsequently devised leading to the articulation of four fundamental ‘idealised’ models of risk communication termed the ‘risk message’ model, the ‘risk dialogue’ model, the ‘risk field’ model and the ‘risk government’ model respectively. It is contended that the diverse conceptual foundations underlying the orientation of each model suggest a further need for a more contextualised view of risk communication that takes account not only of the strengths and limitations of different formulations and functions of risk communication, but also the underlying knowledge/power dynamics that underlie its constitution. In particular it is hoped that the reflexive theoretical understanding presented here will help to bring some much needed conceptual clarity to academic and policy discourses about the use and utility of risk communication in advanced liberal societies

Processes of Strategic Renewal, Competencies, and the Management of Speed

We discuss strategic renewal from a competence perspective. We argue that the management of speed and timing in this process is viewed distinctively when perceived through a cognitive lens. Managers need more firmly grounded process-understanding. The key idea of this paper is to dynamically conceptualize key activities of strategic renewal, and possible sources of break-down as they relate to the managment of speed and timing. Based on a case from the media industry, we identify managerial trade-offs and show how these can be influenced through managing subjective perception, strategic involvement and external knowledge-sourcing.Strategic Renewal, Process, Learning, Knowledge-Sourcing