AI and affordances for mental action

To perceive an affordance is to perceive an object or situation as presenting an opportunity for action. The concept of affordances has been taken up across wide range of disciplines, including AI. I explore an interesting extension of the concept of affordances in robotics. Among the affordances that artificial systems have been engineered to detect are affordances to deliberate. In psychology, affordances are typically limited to bodily action, so the it is noteworthy that AI researchers have found it helpful to extend the concept to encompass mental actions. I propose that psychologists can learn from this extension, and argue that human subjects can perceive mental affordances, such as affordances to attend, affordances to imagine and affordances to count

A context-sensitive conceptual framework for activity modeling

Human motion trajectories, however captured, provide a rich spatiotemporal data source for human activity recognition, and the rich literature in motion trajectory analysis provides the tools to bridge the gap between this data and its semantic interpretation. But activity is an ambiguous term across research communities. For example, in urban transport research activities are generally characterized around certain locations assuming the opportunities and resources are present in that location, and traveling happens between these locations for activity participation, i.e., travel is not an activity, rather a mean to overcome spatial constraints. In contrast, in human-computer interaction (HCI) research and in computer vision research activities taking place along the way, such as reading on the bus, are significant for contextualized service provision. Similarly activities at coarser spatial and temporal granularity, e.g., holidaying in a country, could be recognized in some context or domain. Thus the context prevalent in the literature does not provide a precise and consistent definition of activity, in particular in differentiation to travel when it comes to motion trajectory analysis. Hence in this paper, a thorough literature review studies activity from different perspectives, and develop a common framework to model and reason human behavior flexibly across contexts. This spatio-temporal framework is conceptualized with a focus on modeling activities hierarchically. Three case studies will illustrate how the semantics of the term activity changes based on scale and context. They provide evidence that the framework holds over different domains. In turn, the framework will help developing various applications and services that are aware of the broad spectrum of the term activity across contexts

Affordance-based Design Product Evolution Using Customer Feedback

Designers can benefit from involving the user in the product development process. Understanding how users perceive products can help designers make decisions that better accommodate user needs. Though several methods have been created that involve the user at different stages of the design process, there is still no clear connection between user perceptions and product improvements. Affordance Based Design (ABD) provides the theoretical background needed to explore such connections. ABD is a systematic de-sign method that uses the concept of affordances to describe the interactions between users and products. The integration of ABD and genetic algorithms (GAs) is proposed as a way to capture the perceptions from users in the form of affordance quality evaluations. This research investigates how those user perceptions can be used to improve or evolve product variants. A design tool is developed to test product evolution with the proposed ABD/GA integration. The affordance based interactive genetic algorithm (ABIGA) lets designers capture user perceptions of products. In this tool, designers must specify the design pa-rameters of the product as well as some of its affordances. Users can access design exper-iments from their computers or smart phones and are shown a representation of the prod-uct they evaluate. A set of six experiments were carried to test the evolution of a steering wheel. Three of these experiments were done with real users while the rest were done us-ing a random number generator as the input. Two additional experiments were done with real users to test the evolution of a compact digital camera. Results show that product form can be evolved toward better solutions based on the perceptions of users. The results can also link user perceptions with the form of the product. Designers can extract relationships between affordance evaluations and design parameters. Such relationships can be used to predict how changes in the design parameter values can affect user percep-tions of affordance quality. Product evolution through affordance evaluations could eventually be used to not only improve the external geometry of products, but also certain internal aspects of prod-ucts. Such a tool could be used in multiple stages of the design process, taking advantage of optimization tools linked to the concept of affordance to automate aspects of the prod-uct development process

Qualified Affordance-based Design

Function-based approaches are taught by the engineering design community and implemented in practice. The most significant advantage of these approaches is that they can guide the designers to abstract the essential problems from the design requirements, build the function-based models, and consequently provide the direction of the solution. However, due to the lack of a consistent scientific definition on the meaning of the function, these approaches may be contradictory when representing human-centered aspects, features, and non-physical purposes. To address this issue, design researchers have pursued two general directions: (1) broadening the meaning of function and (2) introducing an alternative scientific concept such as \u27affordance\u27 or \u27wirk\u27 to compensate for the weaknesses of the functional descriptions. Research on affordance is the focus in this thesis. Although the term affordance has been introduced in design methodology, some significant details like representation, categorization, and application into mechanical design still need to be further studied. Therefore, this thesis starts by analyzing the ambiguity of function in design to support the necessity of involving affordances, and then reviews and compares the usages of affordance in Human-Computer Interaction (HCI), Artificial Intelligence (AI), design, psychology, and philosophy. The research opportunities are identified from the review and the comparison of the various approaches. One of the opportunities is to qualify the affordance-based design. Therefore, a new categorization of affordances applicable for product design is proposed, including doing and happening Artifact-Artifact Affordances (dAAA and hAAA), doing and happening Artifact-Environment Affordances (dAEA and hAEA), and doing and happening Artifact-User Affordances (dAUA and hAUA)

A Conceptual Model of Exploration Wayfinding: An Integrated Theoretical Framework and Computational Methodology

This thesis is an attempt to integrate contending cognitive approaches to modeling wayfinding behavior. The primary goal is to create a plausible model for exploration tasks within indoor environments. This conceptual model can be extended for practical applications in the design, planning, and Social sciences. Using empirical evidence a cognitive schema is designed that accounts for perceptual and behavioral preferences in pedestrian navigation. Using this created schema, as a guiding framework, the use of network analysis and space syntax act as a computational methods to simulate human exploration wayfinding in unfamiliar indoor environments. The conceptual model provided is then implemented in two ways. First of which is by updating an existing agent-based modeling software directly. The second means of deploying the model is using a spatial interaction model that distributed visual attraction and movement permeability across a graph-representation of building floor plans

ANALYSIS OF SPACE, COGNITION AND PEDESTRIAN MOVEMENT

Understanding the movement of people in urban areas is one of the most significant issues on spatial science with a wide range of applications in urban design, public health, public safety and intelligent transportation system. Urban planners, cognitive scientists, computer engineers, and geographers have contributed to an understanding of pedestrian movement from aspects of configurational analysis, knowledge representation, computational models, and space-time patterns respectively. However, no previous studies provide comprehensive solutions to pedestrian movement taking both space and cognition into account. Combining these disciplines allows us as researchers to not only explain correlations between spatial layouts and pedestrian flows but also understand how and why environmental perception and spatial knowledge are used by pedestrians to orient themselves and navigate through space. My research proposes a theoretical framework of space, cognition and movement to fill in interdisciplinary gaps of pedestrian movement studies. The core of this framework lies in the hypothesis that where people choose to hold activities and how people choose to get there depends on individuals’ cognitive maps of the environment. This cognitive map consists of the salient layout of spatial features as well as the prominent utilities afforded by these features. The analysis proceeds from three dimensions: (1) space syntax to characterize spatial configuration or structure, (2) space semantics to address the distribution of activities, and (3) spatial cognition to capture one’s knowledge about the space. The proposed framework was used to guide an empirical study conducted at the University of Oklahoma Norman Campus. Space was characterized by two aspects of space syntax and space semantics. For syntactical analysis, the study not only used measures of network centrality to examine network effects on pedestrian movement but also improved them by varying concepts of distance, adding distance decay effects, and weighting spatial heterogeneity of activities. Betweenness centrality calculated by the shortest length and weighted by distance decay effects resulted in the best description of observed pedestrian flows. In semantical analysis, functional centrality was described by density and diversity. Only functional density significantly contributed to modeling pedestrian flows. This study provided evidence that pedestrian movement depended on the spatio-functional interactions. The distribution of activities not only took the location advantage provided by spatial configuration but also reinforced network effects on pedestrian movement. This study not only examined aggregated patterns of pedestrian movement but also investigated individual variations in cognitive maps and wayfinding behaviors. The sketch map analysis suggested that as people became more familiar with the environment, the increase of completeness and accuracy was observed in their cognitive maps. Completeness was described by number of landmarks in sketch maps while accuracy concentrated on the relative positions between pairs of landmarks. Landmark served as the organizing concept of cognitive map. Betweenness centrality, functional density, and familiarity significantly contributed to modeling the presence of landmarks. When landmarks were used in navigation, this study developed a landmark-based pathfinding method. Landmark-based pathfinding resulted in a better description of routes selected by survey participants. In sum, individual cognitive maps, particularly the organization of landmarks, serve as the core in determining where pedestrians choose to hold activities and how to get there. Finally, the study developed the conceptual agent-based model (ABM) for pedestrian movement. The core of this ABM lies in a cognizing agent that is able to solve pathfinding tasks based on perceptual information and knowledge of cognitive map. The research outcomes not only improve the understanding of spatial and cognitive factors on pedestrian wayfinding but also contribute to several disciplines. Architects and urban planners can adopt the framework of pedestrian movement to test, assess and improve existing spatial layouts and possible design alternatives. Computer scientists and Geographic Information System developers can use the specification of cognitive map to implement landmark based navigation system. Cognitive scientists and psychologists can apply the comprehensive model of pedestrian movement in research on human wayfinding behaviors for people with different perceptual abilities

Un modèle multi-agents pour la représentation de l'action située basé sur l'affordance et la stigmergie

Simulation modelling of complex systems nowadays is an ideal solution to get a good understanding of these systems. In effect, compared with real experiments in the field of studies considered, virtual experiments allow one to quickly answer questions about these systems and provide solutions within a delay well adapted to their actual context. This thesis deals with the issue of human action representation, accounting with its temporal and spatial dimensions at individual and collective levels. This question has already been addressed in the field of Artificial intelligence in general and in the one of Agricultural systems in particular, the latter being the application domain of this thesis. The models proposed to date were mainly based upon the theory of planned action, explicitly accounting with the temporal dimension of action only. The main limits of these models lie in their complexity, because the ability to predict all future changes in actors' behaviors is far too difficult. This difficulty leads to the need of frequently re-planning the course of actions in order to get consistent results. The second drawback lies in the discrepancy that may arise between the results of simulated actions and actual observations. In effect, real actors do not realize systematically the actions they forecast according to the situations they actually encounter. In order to overcome the limits of planning models, we developed a model of human action based on the theory of situated action. Action is there viewed as a process endowed with a temporal thickness and emerging from the situations created by the interaction, through time and space, between the actor and its environment. Our model combines the concepts of affordance and stigmergy as well as the notion of emergence. Therefore we propose a multi-agents system within which space is explicitly represented and partitioned into a set of “places”. The control of each place is left to an abstract agent standing for an observer capable of detecting the affordances occurring on its place and trigger appropriate actions. Actors as well as passive objects are represented as “environmental entities”. These entities carry information about their capacity of performing or undergoing actions. This information allows the agents to detect affordances thanks to the meta-knowledge they hold. Once detected, these affordances are reified in the environment to be used to determine the action that will eventually be executed. Coordination of actions, at the collective level, is performed through stigmergy: the agents communicate implicitly between them using a set of marks as a metaphor of pheromons in ant colonies. To prove the relevance of the proposed model, a software prototype, applied to the domain of agricultural production systems, has been implemented with the simulation platform AnyLogic.La modélisation et la simulation des systèmes complexes constitue une solution idéal pour comprendre ces systèmes. En effet, l'expérimentation virtuelle permet, par rapport à l'expérimentation réelle dans le champ d'étude considéré, d'apporter des réponses plus rapides aux questions posées sur ces systèmes, ce qui donne la possibilité de proposer des solutions en un temps adapté au contexte réel. Ce travail traite la question de la représentation de l'action humaine en prenant en compte sa dimension temporelle et spatiale aux échelles individuelle et collective. Cette question a déjà été traitée dans le domaine de l'intelligence artificielle, en général, et celui des systèmes agricoles, en particulier, qui constitue le domaine d'application de cette thèse. Les modèles proposés jusqu'à présent se basaient principalement sur la théorie de l'action planifiée en ne prenant en compte que la dimension temporelle de l'action. Les limites majeures de ces modèles résident dans leur complexité dans la mesure où il est difficile de pouvoir prédire l'ensemble des changements futurs dans l'environnement de l'acteur. Cela conduit à la nécessité de re-planifier fréquemment les actions afin d'obtenir des résultats cohérents. La deuxième limite réside dans l'écart qu'il peut y avoir entre les résultats des actions simulées et la réalité observée. En effet, un acteur ne réalise pas systématiquement les actions qu'il prévoit selon les situations réelles dans lesquelles il se trouve. Afin de pallier aux limites des modèles de l'action planifiée, nous avons développé un modèle de l'action humaine qui se base sur la théorie de l'action située. L'action est vue comme un processus doté d'une épaisseur temporelle émergent des situations créées par l'interaction entre l'acteur et son environnement dans le temps et dans l'espace. Notre modèle combine le concept d'affordance, le concept de stigmergie ainsi que la notion d'émergence. Nous proposons donc un système multi-agents dans lequel l'espace est explicitement représenté et partitionné en un ensemble de places. Le pilotage de chaque place est attribué à un agent abstrait. Celui-ci représente un observateur capable de détecter à tout instant les affordances émergentes sur sa place ainsi que de déclencher l'action appropriée. Les acteurs sont représentés comme des entités de l'environnement au même titre que les objets passifs. Ces entités de l'environnement portent un ensemble d'informations sur leurs capacités à exécuter ou subir des actions. Ces informations permettent aux agents, grâce aux méta-connaissances qu'ils détiennent de détecter les affordances. Celles-ci, une fois détectées, sont réifiées dans l'environnement et utilisées par les agents grâce à un mécanisme de sélection d'actions pour déterminer l'action qui sera finalement exécuter. La coordination des actions au niveau collectif se fait par stigmergie : les agents communiquent de façon implicite en utilisant un ensemble de marques qui sont une métaphore des phéromones des colonies de fourmis. Afin de montrer la pertinence du modèle proposé, un prototype appliqué au domaine des systèmes de production agricoles a été implémenté en utilisant la plateforme AnyLogic