Relevance Grounding for Planning in Relational Domains

Abstract. Probabilistic relational models are an efficient way to learn and represent the dynamics in realistic environments consisting of many objects. Autonomous intelligent agents that ground this representation for all objects need to plan in exponentially large state spaces and large sets of stochastic actions. A key insight for computational efficiency is that successful planning typically involves only a small subset of relevant objects. In this paper, we introduce a probabilistic model to represent planning with subsets of objects and provide a definition of object relevance. Our definition is sufficient to prove consistency between repeated planning in partially grounded models restricted to relevant objects and planning in the fully grounded model. We propose an algorithm that exploits object relevance to plan efficiently in complex domains. Empirical results in a simulated 3D blocksworld with an articulated manipulator and realistic physics prove the effectiveness of our approach.

Embodied cognitive ecosophy: the relationship of mind, body, meaning and ecology

The concept of embodied cognition has had a major impact in a number of disciplines. The extent of its consequences on general knowledge and epistemology are still being explored. Embodied cognition in human geography has its own traditions and discourses but these have become somewhat isolated in the discipline itself. This paper argues that findings in other disciplines are of value in reconceptualising embodied cognition in human geography and this is explored by reconsidering the concept of ecosophy. Criticisms of ecosophy as a theory are considered and recent work in embodied cognition is applied to consider how such criticisms might be addressed. An updated conceptualisation is proposed, the embodied cognitive ecosophy, and three characteristics arising from this criticism and synthesis are presented with a view to inform future discussions of ecosophy and emotional geography

Relational Approach to Knowledge Engineering for POMDP-based Assistance Systems as a Translation of a Psychological Model

Assistive systems for persons with cognitive disabilities (e.g. dementia) are difficult to build due to the wide range of different approaches people can take to accomplishing the same task, and the significant uncertainties that arise from both the unpredictability of client's behaviours and from noise in sensor readings. Partially observable Markov decision process (POMDP) models have been used successfully as the reasoning engine behind such assistive systems for small multi-step tasks such as hand washing. POMDP models are a powerful, yet flexible framework for modelling assistance that can deal with uncertainty and utility. Unfortunately, POMDPs usually require a very labour intensive, manual procedure for their definition and construction. Our previous work has described a knowledge driven method for automatically generating POMDP activity recognition and context sensitive prompting systems for complex tasks. We call the resulting POMDP a SNAP (SyNdetic Assistance Process). The spreadsheet-like result of the analysis does not correspond to the POMDP model directly and the translation to a formal POMDP representation is required. To date, this translation had to be performed manually by a trained POMDP expert. In this paper, we formalise and automate this translation process using a probabilistic relational model (PRM) encoded in a relational database. We demonstrate the method by eliciting three assistance tasks from non-experts. We validate the resulting POMDP models using case-based simulations to show that they are reasonable for the domains. We also show a complete case study of a designer specifying one database, including an evaluation in a real-life experiment with a human actor

Consciosusness in Cognitive Architectures. A Principled Analysis of RCS, Soar and ACT-R

This report analyses the aplicability of the principles of consciousness developed in the ASys project to three of the most relevant cognitive architectures. This is done in relation to their aplicability to build integrated control systems and studying their support for general mechanisms of real-time consciousness.\ud To analyse these architectures the ASys Framework is employed. This is a conceptual framework based on an extension for cognitive autonomous systems of the General Systems Theory (GST).\ud A general qualitative evaluation criteria for cognitive architectures is established based upon: a) requirements for a cognitive architecture, b) the theoretical framework based on the GST and c) core design principles for integrated cognitive conscious control systems

Crossmodal content binding in information-processing architectures

Operating in a physical context, an intelligent robot faces two fundamental problems. First, it needs to combine information from its different sensors to form a representation of the environment that is more complete than any of its sensors on its own could provide. Second, it needs to combine high-level representations (such as those for planning and dialogue) with its sensory information, to ensure that the interpretations of these symbolic representations are grounded in the situated context. Previous approaches to this problem have used techniques such as (low-level) information fusion, ontological reasoning, and (high-level) concept learning. This paper presents a framework in which these, and other approaches, can be combined to form a shared representation of the current state of the robot in relation to its environment and other agents. Preliminary results from an implemented system are presented to illustrate how the framework supports behaviours commonly required of an intelligent robot

Supply chain management as the key to a firm’s strategy in the global marketplace

Purpose: This research aims to analyze the intersection of two literature streams: that of strategy and supply chain management (SCM). This review should create a better understanding of “strategic SCM” by focusing on relevant theories in the strategic management field and their intersection with SCM to develop a joint research agenda. Design/Methodology/Approach: We conducted a correspondence analysis on the content of 3,402 articles from the top SCM journals. This analysis provides a map of the intellectual structure of content in this field to date. The key trends and changes were identified in strategic SCM research from 1990-2014 as well as the intersection with the key schools of strategic management. Findings: The results suggest that SCM is key to a successful deployment of strategy for competing in the global marketplace. The main theoretical foundations for research in this field were identified and discussed. Gaps were detected and combinations of theoretical foundations of strategic management and SCM suggest four poles for future research: agents and focal firm; distributions and logistics strategic models; SCM competitive requirements; SCM relational governance. Research limitations/implications: Scholars in both the strategy and the SCM fields continue to search for competitive advantages. Much recent research indicates that strategic SCM can be a critical source for that advantage. One of the limitations of our research is that the analysis does not include every journal that published an article mentioning SCM. However, the 34 journals selected are reputed to be the most influential on SCM and focused primarily on SCM. Practical implications: The map of the intellectual structure of research to strategic SCM highlights the need to combine different theoretical approaches to the complex phenomenon of SCM. Practitioners should consider the supply chain as an informal organization and should devote time and resources to build a shared advantage across the supply chain. They should also consider the inherent benefits and risks that sharing Originality/value: The paper demonstrates that strategic SCM needs a balanced and rigorous combination of theoretical approaches to deliver more theory-driven evidences. Our research combines both a qualitative analysis and a quantitative methodology that summarizes gaps and then outlines future research from a large sample of articles. This methodology is an original contribution to this field and offers some assistance for enlarging the sample of future literature reviews