Searcharxiv⌕ Search

arXiv subjects

Ladislau Bölöni

Publications and source records attributed to Ladislau Bölöni.

22 records · Page 2Linked to original sources

Towards a computational model of social norms

We describe a computational model of social norms based on identifying values that a certain culture finds desirable such as dignity, generosity and politeness. The model quantifies these values in the form of Culture-Sanctioned Social Metrics (CSSMs) and treats social norms as the requirement to maximize these metrics from the perspective of the self, peers and public. This model can be used to create realistic social simulations, to explain or predict human behavior in specific scenarios, or as a component of robots or agents that need to interact with humans in specific social-cultural settings. We validate the model by using it to represent a complex deception scenario and showing that it can yield non-trivial insights such as the explanation of apparently irrational human behavior.

cs.CY↗

From virtual demonstration to real-world manipulation using LSTM and MDN

Robots assisting the disabled or elderly must perform complex manipulation tasks and must adapt to the home environment and preferences of their user. Learning from demonstration is a promising choice, that would allow the non-technical user to teach the robot different tasks. However, collecting demonstrations in the home environment of a disabled user is time consuming, disruptive to the comfort of the user, and presents safety challenges. It would be desirable to perform the demonstrations in a virtual environment. In this paper we describe a solution to the challenging problem of behavior transfer from virtual demonstration to a physical robot. The virtual demonstrations are used to train a deep neural network based controller, which is using a Long Short Term Memory (LSTM) recurrent neural network to generate trajectories. The training process uses a Mixture Density Network (MDN) to calculate an error signal suitable for the multimodal nature of demonstrations. The controller learned in the virtual environment is transferred to a physical robot (a Rethink Robotics Baxter). An off-the-shelf vision component is used to substitute for geometric knowledge available in the simulation and an inverse kinematics module is used to allow the Baxter to enact the trajectory. Our experimental studies validate the three contributions of the paper: (1) the controller learned from virtual demonstrations can be used to successfully perform the manipulation tasks on a physical robot, (2) the LSTM+MDN architectural choice outperforms other choices, such as the use of feedforward networks and mean-squared error based training signals and (3) allowing imperfect demonstrations in the training set also allows the controller to learn how to correct its manipulation mistakes.

cs.RO↗

A cookbook of translating English to Xapi

The Xapagy cognitive architecture had been designed to perform narrative reasoning: to model and mimic the activities performed by humans when witnessing, reading, recalling, narrating and talking about stories. Xapagy communicates with the outside world using Xapi, a simplified, "pidgin" language which is strongly tied to the internal representation model (instances, scenes and verb instances) and reasoning techniques (shadows and headless shadows). While not fully a semantic equivalent of natural language, Xapi can represent a wide range of complex stories. We illustrate the representation technique used in Xapi through examples taken from folk physics, folk psychology as well as some more unusual literary examples. We argue that while the Xapi model represents a conceptual shift from the English representation, the mapping is logical and consistent, and a trained knowledge engineer can translate between English and Xapi at near-native speed.

cs.AI↗

Xapagy: a cognitive architecture for narrative reasoning

We introduce the Xapagy cognitive architecture: a software system designed to perform narrative reasoning. The architecture has been designed from scratch to model and mimic the activities performed by humans when witnessing, reading, recalling, narrating and talking about stories.

cs.AI↗