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Towards Developing Probabilistic Generative Models for Reasoning with Natural Language Representations [chapter]

Daniel Marcu, Ana-Maria Popescu
2005 Lecture Notes in Computer Science  
text-based deduction and abduction decoding algorithms.  ...  Summarization beyond sentence extraction: A probabilistic approach to sentence compression. Artificial Intelligence 139(1): 91-107. Lin Dekang. 1995. MINIPAR. A Dependency-Based Parser.  ...  ., the most probable ways to rewrite the effect string "PEOPLE die" into a cause string are those listed in Table 1 As one can see, many of these learned causes are intuitively correct.  ... 
doi:10.1007/978-3-540-30586-6_8 fatcat:o2525f5wl5h63lboa3al2pb7tm

Probabilistic extraction and discovery of fundamental units in dolphin whistles

Daniel Kohlsdorf, Celeste Mason, Denise Herzing, Thad Starner
2014 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)  
Furthermore, we investigate discovery algorithms for fundamental units using a mixture of hidden Markov models. We evaluate our findings with a marine mammalogist on data collected in the field.  ...  We propose a method for whistle extraction from noisy underwater recordings using a probabilistic approach.  ...  CONCLUSION We presented a novel system for whistle extraction using a probabilistic algorithm and a novel pattern detector algorithm.  ... 
doi:10.1109/icassp.2014.6855208 dblp:conf/icassp/KohlsdorfMHS14 fatcat:2qm2ursgxjcehjrjpl6t2hua44

Plan recognition in exploratory domains

Ya'akov Gal, Swapna Reddy, Stuart M. Shieber, Andee Rubin, Barbara J. Grosz
2012 Artificial Intelligence  
This paper describes a challenging plan recognition problem that arises in environments in which agents engage widely in exploratory behavior, and presents new algorithms for effective plan recognition  ...  Classical approaches to plan recognition have assumed a goal-oriented agent whose activities are consistent with the recognizers' knowledge base and who forms a single encompassing plan.  ...  A special thanks goes to Ofra Amir for reading and commenting on previous drafts of this work.  ... 
doi:10.1016/j.artint.2011.09.002 fatcat:v6hrgok7vjbtvnvnr62inoticq

Page 5363 of Mathematical Reviews Vol. , Issue 90I [page]

1990 Mathematical Reviews  
Kucherov, A new quasi-reducibility testing algorithm and its application to proofs by induction (pp. 204-213); Dong Bo Liu and De Yi Li, Fuzzy reasoning based on f-Horn clause rules (pp. 214-222); Juan  ...  Luc Devroye, Probabilistic analysis of algorithms and data struc- tures (p. 230); Michael T.  ... 

Recognition of multi-agent interaction in video surveillance

Y.A. Ivanov, A.F. Bobick
1999 Proceedings of the Seventh IEEE International Conference on Computer Vision  
This paper describes a probabilistic syntactic approach to the detection and recognition of temporally extended activities and interactions between multiple agents.  ...  The main contributions of this paper are extending the parsing algorithm to handle multi-agent interactions within a single parser, providing a general mechanism for consistency-based pruning, and developing  ...  Based on appearance and trajectory properties, the tracker probabilistically assigns to each object a class label (a car or a person).  ... 
doi:10.1109/iccv.1999.791214 dblp:conf/iccv/IvanovB99 fatcat:vp3j54lgxffvjb5crir6pfufjq

Bypassing Words in Automatic Speech Recognition

Paul De Palma, George Luger, Caroline Smith, Charles Wooters
2012 Midwest Artificial Intelligence and Cognitive Science Conference  
concept model that transforms syllable strings to concept strings, where a concept collects related words and phrases.  ...  The paper presents preliminary positive results on the use of syllables and concepts in speech recognition and outlines our current efforts to verify the Syllable-Concept Hypothesis (SCH).  ...  Background The goal of probabilistic speech recognition is to answer this question: "What is the most likely string of words, W, from a language, L, given some acoustic input, A."  ... 
dblp:conf/maics/PalmaLSW12 fatcat:rcifgtahzreh5jnk3v5u2dwlie

Integrating generative growth and evolutionary computation for form exploration

Una-May O'Reilly, Martin Hemberg
2007 Genetic Programming and Evolvable Machines  
We have developed a complementary Evolutionary Algorithm (EA) that is able to take over the task of generating the rewrite rules set for a growth process.  ...  This growth process relies upon a set of rewrite rules, a map axiom and a novel geometrical interpreter which is integrated with a 3D simulated environment.  ...  L-systems are based on rewrite systems, a concept invented by Thue [2] . A rewrite system consists of a seed and a number of rewrite rules that are repeatedly applied to the string.  ... 
doi:10.1007/s10710-007-9025-y fatcat:pw6yzg5babgi7l5i2xxea3ekfm

A probabilistic plan recognition algorithm based on plan tree grammars

Christopher W. Geib, Robert P. Goldman
2009 Artificial Intelligence  
We present the PHATT algorithm for plan recognition. Unlike previous approaches to plan recognition, PHATT is based on a model of plan execution.  ...  We present the PHATT algorithm's theoretical basis, and an implementation based on tree structures. We also investigate the algorithm's complexity, both analytically and empirically.  ...  Acknowledgments This article was supported by DARPA/IPTO and and the Air Force Research Laboratory, Wright Labs under contract number FA8650-06-C-7606, and based upon earlier work supported by DARPA/ITO  ... 
doi:10.1016/j.artint.2009.01.003 fatcat:nbbpt7utmrdm3ln2i7tbjdgc74

A Probabilistic Learning Method for XML Annotation of Documents

Boris Chidlovskii, Jérôme Fuselier
2005 International Joint Conference on Artificial Intelligence  
In the probabilistic setting, we cope with the tree annotation problem as a generalized probabilistic context-free parsing of an observation sequence where each observation comes with a probability distribution  ...  over terminals supplied by a probabilistic classifier associated with the content of documents.  ...  The binarization rewrites any rule A → B C D as two rules A → BP and P → C D, where P is a new non-terminal.  ... 
dblp:conf/ijcai/ChidlovskiiF05 fatcat:l2l5njwl4jh3bpqlyk5qyndzwe

Generalized queries on probabilistic context-free grammars

D.V. Pynadath, M.P. Wellman
1998 IEEE Transactions on Pattern Analysis and Machine Intelligence  
We present an algorithm for constructing Bayesian networks from PCFGs, and show how queries or patterns of queries on the network correspond to interesting queries on PCFGs.  ...  Index Terms-Probabilistic context-free grammars, Bayesian networks. ----------3 ---------- PROBABILISTIC CONTEXT-FREE GRAMMARS A probabilistic context-free grammar is a tuple Â, , , N S P , where the disjoint  ...  Both algorithms require time O(L 3 ) for a string of length L, ignoring the dependency on the size of the grammar.  ... 
doi:10.1109/34.655650 fatcat:cp2czsk3a5bbtd6dt6gqynpylq

10 Years of Probabilistic Querying – What Next? [chapter]

Martin Theobald, Luc De Raedt, Maximilian Dylla, Angelika Kimmig, Iris Miliaraki
2013 Lecture Notes in Computer Science  
While probabilistic databases have focused on describing tractable query classes based on the structure of query plans and data lineage, probabilistic programming has contributed sophisticated inference  ...  techniques based on knowledge compilation and lifted (first-order) inference.  ...  While ProbLog uses a single type of target structure that is independent of the query structure, work in PDBs has more explicitly considered different classes of query structures, based on query plans  ... 
doi:10.1007/978-3-642-40683-6_1 fatcat:lofuquzqgbb4hcjtjeqydyakbe

A Survey and Analysis of Techniques for Player Behavior Prediction in Massively Multiplayer Online Role-Playing Games

Brent Harrison, Stephen G. Ware, Matthew W. Fendt, David L. Roberts
2015 IEEE Transactions on Emerging Topics in Computing  
In order to demonstrate the value of our analysis, we present a case study from our own work that uses a model-based collaborative filtering algorithm to predict achievements in World of Warcraft.  ...  In this paper, we survey and evaluate three classes of player modeling techniques: 1) manual tagging; 2) collaborative filtering; and 3) goal recognition.  ...  Goal recognition techniques can be broadly divided into two types: those based on planning systems and those based VOLUME 3, NO. 2, JUNE 2015 on probabilistic models.  ... 
doi:10.1109/tetc.2014.2360463 fatcat:bll2mpkj7bgqllkxfxwckexkje

Learning to learn generative programs with Memoised Wake-Sleep [article]

Luke B. Hewitt and Tuan Anh Le and Joshua B. Tenenbaum
2020 arXiv   pre-print
We use MWS to learn accurate, explainable models in three challenging domains: stroke-based character modelling, cellular automata, and few-shot learning in a novel dataset of real-world string concepts  ...  To tackle the challenge of performing program induction as an 'inner-loop' to learning, we propose the Memoised Wake-Sleep (MWS) algorithm, which extends Wake Sleep by explicitly storing and reusing the  ...  In character recognition, the stroke-based model of Lake et al.  ... 
arXiv:2007.03132v2 fatcat:rjh3ikcmdrb2hnbzzcat6evzba

State-Space Abstractions for Probabilistic Inference: A Systematic Review [article]

Stefan Lüdtke, Max Schröder, Frank Krüger, Sebastian Bader, Thomas Kirste
2018 arXiv   pre-print
Furthermore, we provide new high-level categories that classify the approaches, based on common properties of the approaches.  ...  However, standard probabilistic inference algorithms work at a propositional level, and thus cannot capture the symmetries and redundancies that are present in these tasks.  ...  model recursive bayesian estimation bayesian filtering particle filter hidden markov model probabilistic multiset rewriting multi-agent multi-target multi-object activity recognition plan recognition  ... 
arXiv:1804.06748v2 fatcat:yj2eafizonaqvcg7k4e24tacya

Abstractions for AI-Based User Interfaces and Systems [article]

Alex Renda, Harrison Goldstein, Sarah Bird, Chris Quirk, Adrian Sampson
2017 arXiv   pre-print
Novel user interfaces based on artificial intelligence, such as natural-language agents, present new categories of engineering challenges.  ...  Second, a feature type system abstracts the interaction between applications and learning algorithms.  ...  INTRODUCTION Rapid progress in machine learning has sparked a stampede toward new kinds of user interfaces based on natural interaction.  ... 
arXiv:1709.04991v1 fatcat:4uxcpaxzifh7te6niuus5b56cq
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