Herbert Simon's decision-making approach: Investigation of cognitive processes in experts

This is a post print version of the article. The official published can be obtained from the links below - PsycINFO Database Record (c) 2010 APA, all rights reserved.Herbert Simon's research endeavor aimed to understand the processes that participate in human decision making. However, despite his effort to investigate this question, his work did not have the impact in the “decision making” community that it had in other fields. His rejection of the assumption of perfect rationality, made in mainstream economics, led him to develop the concept of bounded rationality. Simon's approach also emphasized the limitations of the cognitive system, the change of processes due to expertise, and the direct empirical study of cognitive processes involved in decision making. In this article, we argue that his subsequent research program in problem solving and expertise offered critical tools for studying decision-making processes that took into account his original notion of bounded rationality. Unfortunately, these tools were ignored by the main research paradigms in decision making, such as Tversky and Kahneman's biased rationality approach (also known as the heuristics and biases approach) and the ecological approach advanced by Gigerenzer and others. We make a proposal of how to integrate Simon's approach with the main current approaches to decision making. We argue that this would lead to better models of decision making that are more generalizable, have higher ecological validity, include specification of cognitive processes, and provide a better understanding of the interaction between the characteristics of the cognitive system and the contingencies of the environment

Model-Based Environmental Visual Perception for Humanoid Robots

The visual perception of a robot should answer two fundamental questions: What? and Where? In order to properly and efficiently reply to these questions, it is essential to establish a bidirectional coupling between the external stimuli and the internal representations. This coupling links the physical world with the inner abstraction models by sensor transformation, recognition, matching and optimization algorithms. The objective of this PhD is to establish this sensor-model coupling

Indexing Techniques for Image and Video Databases: an approach based on Animate Vision Paradigm

[ITALIANO]In questo lavoro di tesi vengono presentate e discusse delle innovative tecniche di indicizzazione per database video e di immagini basate sul paradigma della “Animate Vision” (Visione Animata). Da un lato, sarà mostrato come utilizzando, quali algoritmi di analisi di una data immagine, alcuni meccanismi di visione biologica, come i movimenti saccadici e le fissazioni dell'occhio umano, sia possibile ottenere un query processing in database di immagini più efficace ed efficiente. In particolare, verranno discussi, la metodologia grazie alla quale risulta possibile generare due sequenze di fissazioni, a partire rispettivamente, da un'immagine di query I_q ed una di test I_t del data set, e, come confrontare tali sequenze al fine di determinare una possibile misura della similarità (consistenza) tra le due immagini. Contemporaneamente, verrà discusso come tale approccio unito a tecniche classiche di clustering possa essere usato per scoprire le associazioni semantiche nascoste tra immagini, in termini di categorie, che, di contro, permettono un'automatica pre-classificazione (indicizzazione) delle immagini e possono essere usate per guidare e migliorare il processo di query. Saranno presentati, infine, dei risultati preliminari e l'approccio proposto sarà confrontato con le più recenti tecniche per il recupero di immagini descritte in letteratura. Dall'altro lato, sarà mostrato come utilizzando la precedente rappresentazione “foveata” di un'immagine, risulti possibile partizionare un video in shot. Più precisamente, il metodo per il rilevamento dei cambiamenti di shot si baserà sulla computazione, in ogni istante di tempo, della misura di consistenza tra le sequenze di fissazioni generate da un osservatore ideale che guarda il video. Lo schema proposto permette l'individuazione, attraverso l'utilizzo di un'unica tecnica anziché di più metodi dedicati, sia delle transizioni brusche sia di quelle graduali. Vengono infine mostrati i risultati ottenuti su varie tipologie di video e, come questi, validano l'approccio proposto. / [INGLESE]In this dissertation some novel indexing techniques for video and image database based on “Animate Vision” Paradigm are presented and discussed. From one hand, it will be shown how, by embedding within image inspection algorithms active mechanisms of biological vision such as saccadic eye movements and fixations, a more effective query processing in image database can be achieved. In particular, it will be discussed the way to generate two fixation sequences from a query image I_q and a test image I_t of the data set, respectively, and how to compare the two sequences in order to compute a possible similarity (consistency) measure between the two images. Meanwhile, it will be shown how the approach can be used with classical clustering techniques to discover and represent the hidden semantic associations among images, in terms of categories, which, in turn, allow an automatic pre-classification (indexing), and can be used to drive and improve the query processing. Eventually, preliminary results will be presented and the proposed approach compared with the most recent techniques for image retrieval described in the literature. From the other one, it will be discussed how by taking advantage of such foveated representation of an image, it is possible to partitioning of a video into shots. More precisely, the shot-change detection method will be based on the computation, at each time instant, of the consistency measure of the fixation sequences generated by an ideal observer looking at the video. The proposed scheme aims at detecting both abrupt and gradual transitions between shots using a single technique, rather than a set of dedicated methods. Results on videos of various content types are reported and validate the proposed approach

Human Action Recognition and Monitoring in Ambient Assisted Living Environments

Population ageing is set to become one of the most significant challenges of the 21st century, with implications for almost all sectors of society. Especially in developed countries, governments should immediately implement policies and solutions to facilitate the needs of an increasingly older population. Ambient Intelligence (AmI) and in particular the area of Ambient Assisted Living (AAL) offer a feasible response, allowing the creation of human-centric smart environments that are sensitive and responsive to the needs and behaviours of the user. In such a scenario, understand what a human being is doing, if and how he/she is interacting with specific objects, or whether abnormal situations are occurring is critical. This thesis is focused on two related research areas of AAL: the development of innovative vision-based techniques for human action recognition and the remote monitoring of users behaviour in smart environments. The former topic is addressed through different approaches based on data extracted from RGB-D sensors. A first algorithm exploiting skeleton joints orientations is proposed. This approach is extended through a multi-modal strategy that includes the RGB channel to define a number of temporal images, capable of describing the time evolution of actions. Finally, the concept of template co-updating concerning action recognition is introduced. Indeed, exploiting different data categories (e.g., skeleton and RGB information) improve the effectiveness of template updating through co-updating techniques. The action recognition algorithms have been evaluated on CAD-60 and CAD-120, achieving results comparable with the state-of-the-art. Moreover, due to the lack of datasets including skeleton joints orientations, a new benchmark named Office Activity Dataset has been internally acquired and released. Regarding the second topic addressed, the goal is to provide a detailed implementation strategy concerning a generic Internet of Things monitoring platform that could be used for checking users' behaviour in AmI/AAL contexts

On-line video abstraction

Tesis doctoral inédita. Universidad Autónoma de Madrid, Escuela Politécnica Superior, abril de 201