OntoAgent
OntoAgent is an agent architecture that supports content-centric modeling.[1] OntoAgent is a platform for developing intelligent agent systems. It consists of a network of processing modules, a content module (consisting of several non-toy knowledge bases), and an infrastructure module that supports system functioning, system integration, and system development activities. OntoAgent fosters developing embodied or simulated intelligent agent models and testing their performance in application systems.
NLU[edit]
NLU in OntoAgent follows the theory of Ontological Semantics (OS; Nirenburg and Raskin 2004). The goal of OS language understanding is to generate contextually disambiguated, ontologically grounded text meaning representations that are stored to agent memory in support of subsequent reasoning about action. Individual linguistic phenomena are treated by microtheories which, at any given time, can be at various stages of advancement both descriptively and in terms of implementation.[2]
The simplest case of language analysis is illustrated by the example A brown squirrel is eating a nut. For this input, like any other, the LEIA must disambiguate each lexeme (that is, understand it as an instance of a particular concept in its ontology) and combine those interpretations into a Text Meaning Representation:
INGEST-1
AGENT SQUIRREL-1
THEME NUT-FOODSTUFF-1
TIME find-anchor-time
SQUIRREL-1
COLOR BROWN
AGENT-OF INGEST-1
NUT-FOODSTUFF-1
THEME-OF INGEST-1
Given our input A brown squirrel is eating a nut, the LEIA links the word squirrel to $var1 then semantically analyzes it as SQUIRREL before using it to fill the AGENT role of INGEST. An analogous process occurs for $var2/^$var2.
A Simplified Version of the INGEST Sense of Eat:
eat-v1: “ingest,” as in “He was eating (cheese).”
syn-struc
subject $var1
root $var0
directobject $var2 (optional)
sem-struc
INGEST
AGENT ^$var1
THEME ^$var2
The ontology, for its part, constrains the valid fillers of the case-roles of INGEST as shown in the following excerpt from the Ontological Frame for INGEST:
INGEST
AGENT
sem ANIMAL
relaxable-to SOCIAL - OBJECT
THEME
sem FOOD , BEVERAGE , INGESTIBLE - MEDICATION
relaxable-to ANIMAL , PLANT
not HUMAN
References[edit]
- ↑ English, Jesse; Nirenburg, Sergei (2017). OntoAgent: Implementing Content-Centric Cognitive Models. Search this book on
- ↑ McShane, Marjorie (2017). "Natural Language Understanding (NLU, not NLP) in Cognitive Systems" (Association for the Advancement of Artificial Intelligence).
Further reading[edit]
- McShane, Marjorie; Nirenburg, Sergei (March 2021). Linguistics for the Age of AI. MIT Press. ISBN 9780262045582. Search this book on
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