A Case for Symbolic/Sub-symbolic Hybrids

This paper considers the question of what qualities are necessary for an AI system to be a hybrid of symbolic and sub-symbolic approaches. Definitions of symbolic and sub-symbolic systems are given. SCALIR, a hybrid system for information retrieval, is presented, and then used to show how both symbolic and sub-symbolic processing can be combined. Arguments against SCALIR's hybrid nature are presented and rejected

Empirical entropic contributions in computational docking: Evaluation in APS reductase complexes

The results from reiterated docking experiments may be used to evaluate an empirical vibrational entropy of binding in ligand–protein complexes. We have tested several methods for evaluating the vibrational contribution to binding of 22 nucleotide analogues to the enzyme APS reductase. These include two cluster size methods that measure the probability of finding a particular conformation, a method that estimates the extent of the local energetic well by looking at the scatter of conformations within clustered results, and an RMSD-based method that uses the overall scatter and clustering of all conformations. We have also directly characterized the local energy landscape by randomly sampling around docked conformations. The simple cluster size method shows the best performance, improving the identification of correct conformations in multiple docking experiments. © 2008 Wiley Periodicals, Inc. J Comput Chem, 2008Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/60220/1/20936_ftp.pd

Improved Evolutionary Hybrids for Flexible Ligand Docking in Autodock

In this paper we evaluate the design of the hybrid evolutionary algorithms (EAs) that are currently used to perform flexible ligand binding in the Autodock docking software. Hybrid EAs incorporate specialized operators that exploit domain-specific features to accelerate an EA's search. We consider hybrid EAs that use an integrated local search operator to reline individuals within each iteration of the search. We evaluate several factors that impact the efficacy of a hybrid EA, and we propose new hybrid EAs that provide more robust convergence to low-energy docking configurations than the methods currently available in Autodock

Adaptive Information Agents in Distributed Textual Environments

Hypertext environments such as the Web are rich with both word and link cues that can be exploited by autonomous agents performing distributed tasks on behalf of the user. This paper characterizes such environments and identifies the features that are most useful and readily available. We describe the adaptive representation of an ecology of retrieval agents who attempt to capture important features of their surroundings, and base their behaviors upon them. We discuss how such a representation allows the agents to interact with the environments where they are situated. Agents can internalize words that are locally correlated with fitness, based on user feedback. They are shown to outperform nonadaptive search by an order of magnitude. Furthermore, each agent learns new strategies at local time and space scales, while the population evolves at a global scale. 1 Introduction Imagine that you just submitted a query to your favorite digital library or search engine on the Web, and receiv..

Coupling Morphology and Control in an Evolved Robot

The history of natural evolution displays an inseparable coupling between organic bodies and the nervous systems that control them. That is, animal nervous systems extend throughout the entire body and it is problematic to separate them for isolated study. In contrast to this almost all research in Evolutionary Robotics to date begins with a robot body whose features are fixed and proceeds to evolve a control structure for this body. Our research program is focused on exploring the coupled evolution of both the body and the control structure in real robots. In this paper we take early steps toward this goal by exploring the space of sensor and effector selection and positioning coupled with a neural network linking them. This space is explored using a single grammar for generating both the body and neural network. Results from several problem worlds are presented and analyzed. 1 INTRODUCTION The most successful agents we know of are those found in real life. These agents are well adap..