45,629 research outputs found
A self-organizing spatial vocabulary
Language is a shared set of conventions for mapping meanings to utterances. This paper explores self-organization as the primary mechanism for the formation of a vocabulary. It reports on a computational experiment in which a group of distributed agents develop ways to identify each other using names or spatial descriptions. It is also shown that the proposed mechanism copes with the acquisition of an existing vocabulary by new agents entering the community and with an expansion of the set of meanings.The research and writing of this paper has been financed by the Belgian Federal government FKFO project on emergent functionality (FKFO contract no. G.0014.95) and the IUAP >Construct> Project (no. 20) of the Belgian government, with additional support from the external researcher program of the Sony Computer Science Laboratory in Tokyo.Peer Reviewe
The role of oblivion, memory size and spatial separation in dynamic language games
In this paper we present some multiagent simulations in which the individuals try to reach a uniform vocabulary to name spatial movements. Each agent has initially a random vocabulary that can be modified by means of interactions with the other agents. As the objective is to name movements, the topic of conversation is chosen by moving. Each agent can remember a finite number of words per movement, with certain strength. We show the importance of the forgetting process and memory size in these simulations, discuss the effect of the number of agents on the time to agree and present a few experiments where the evolution of vocabularies takes place in a divided range.This paper has been sponsored by the Spanish Interdepartmental Commission of Science and Technology (CICYT), project numbers TEL1999-0181, and TIC 2001-0685-C02-01
Some strategies for the simulation of vocabulary agreement in multi-agent communities
In this paper, we present several experiments of belief propagation in multi-agent communities. Each agent in the simulation has an initial random vocabulary (4 words) corresponding to each possible movement (north, south, east and west). Agents move and communicate the associated word to the surrounding agents, which can be convinced by the 'speaking agent', and change their corresponding word by 'imitation'. Vocabulary uniformity is achieved, but strong interactions and competition can occur between dominant words. Several moving and trusting strategies as well as agent roles are analyzed.This paper has been sponsored by the Spanish Interdepartmental Commission of Science and Technology (CICYT), project number TEL1999-0181
Action Recognition in Videos: from Motion Capture Labs to the Web
This paper presents a survey of human action recognition approaches based on
visual data recorded from a single video camera. We propose an organizing
framework which puts in evidence the evolution of the area, with techniques
moving from heavily constrained motion capture scenarios towards more
challenging, realistic, "in the wild" videos. The proposed organization is
based on the representation used as input for the recognition task, emphasizing
the hypothesis assumed and thus, the constraints imposed on the type of video
that each technique is able to address. Expliciting the hypothesis and
constraints makes the framework particularly useful to select a method, given
an application. Another advantage of the proposed organization is that it
allows categorizing newest approaches seamlessly with traditional ones, while
providing an insightful perspective of the evolution of the action recognition
task up to now. That perspective is the basis for the discussion in the end of
the paper, where we also present the main open issues in the area.Comment: Preprint submitted to CVIU, survey paper, 46 pages, 2 figures, 4
table
ARTSCENE: A Neural System for Natural Scene Classification
How do humans rapidly recognize a scene? How can neural models capture this biological competence to achieve state-of-the-art scene classification? The ARTSCENE neural system classifies natural scene photographs by using multiple spatial scales to efficiently accumulate evidence for gist and texture. ARTSCENE embodies a coarse-to-fine Texture Size Ranking Principle whereby spatial attention processes multiple scales of scenic information, ranging from global gist to local properties of textures. The model can incrementally learn and predict scene identity by gist information alone and can improve performance through selective attention to scenic textures of progressively smaller size. ARTSCENE discriminates 4 landscape scene categories (coast, forest, mountain and countryside) with up to 91.58% correct on a test set, outperforms alternative models in the literature which use biologically implausible computations, and outperforms component systems that use either gist or texture information alone. Model simulations also show that adjacent textures form higher-order features that are also informative for scene recognition.National Science Foundation (NSF SBE-0354378); Office of Naval Research (N00014-01-1-0624
A Certain Amount of the Unknown - The Argument of the Bodily in Don DeLillo
Zadanie pt. „Digitalizacja i udostępnienie w Cyfrowym Repozytorium Uniwersytetu Łódzkiego kolekcji czasopism naukowych wydawanych przez Uniwersytet Łódzki” nr 885/P-DUN/2014 dofinansowane zostało ze środków MNiSW w ramach działalności upowszechniającej nauk
Grounded Concept Development Using Introspective Atoms
In this paper we present a system that uses its underlying
physiology, a hierarchical memory and a collection of memory
management algorithms to learn concepts as cases and to
build higher level concepts from experiences represented as
sequences of atoms. Using a memory structure that requires
all base memories to be grounded in introspective atoms, the
system builds a set of grounded concepts that must all be
formed from and applied to this same set of atoms. All interaction the system has with its environment must be represented by the system itself and therefore, given a complete ability to perceive its own physiological and mental processes,can be modeled and recreated
- …