scholarly journals Interactive Fiction Games: A Colossal Adventure

2020 ◽  
Vol 34 (05) ◽  
pp. 7903-7910
Author(s):  
Matthew Hausknecht ◽  
Prithviraj Ammanabrolu ◽  
Marc-Alexandre Côté ◽  
Xingdi Yuan
Keyword(s):  
Autonomous Agents ◽  
Rapid Development ◽  
Human Intelligence ◽  
Commonsense Reasoning ◽  
Interactive Fiction ◽  
Language Understanding ◽  
Effect Change ◽  
Development Of Language ◽  
Action Spaces ◽  
Comprehensive Study

A hallmark of human intelligence is the ability to understand and communicate with language. Interactive Fiction games are fully text-based simulation environments where a player issues text commands to effect change in the environment and progress through the story. We argue that IF games are an excellent testbed for studying language-based autonomous agents. In particular, IF games combine challenges of combinatorial action spaces, language understanding, and commonsense reasoning. To facilitate rapid development of language-based agents, we introduce Jericho, a learning environment for man-made IF games and conduct a comprehensive study of text-agents across a rich set of games, highlighting directions in which agents can improve.

Professional Information Needs of Library Specialists in Russia

2021 ◽  
Vol 70 (1) ◽  
pp. 7-20
Author(s):  
Marina Y. Neshcheret
Keyword(s):  
Information Needs ◽  
Rapid Development ◽  
Information Service ◽  
Library Science ◽  
Information Process ◽  
Cultural Workers ◽  
Use Of Resources ◽  
The Creation ◽  
Professional Information ◽  
Comprehensive Study

The article is devoted to the comprehensive study of the professional information needs (IN) of specialists of the central libraries of the subjects of the Russian Federation. The rapid development of high technologies in the field of accumulation, transmission and processing of information, the creation of modern telecommunications systems have led to the emergence of fundamentally new opportunities for organizing the information process. This, in turn, led to the qualitative growth of IN specialists, including those employed in the field of library activities. The specific features of IN library specialists are determined by their place and role in the modern process of cultural activity, industry orientation, nature of work and specialization. During 2018—2019, the Centre for Research of Problems of the Development of Libraries in the Information Society of the Russian State Library carried out research aimed at comprehensive study of the information needs of cultural workers employed in the library sphere. At the first stage of the research, there was comprehended the existing experience of studying professional information needs in the national library science. At the second stage, using the method of questionnaire survey, information needs of library specialists were studied in order to identify the most rational forms and methods of providing them. The analysis of the survey results made it possible to identify the sources of professional information, to reveal information resources that have the greatest importance and characterize specific features of librarians’ information needs.The author concludes on the need to expand the access to full-text databases and electronic versions of periodicals for library staff. The creation of integrated information centre could help providing library professionals with professional information. Currently, the function of such a centre is performed by the National Electronic Library, which includes the professional section for library specialists. The results of the study form theoretical and methodological basis for the rational use of resources and potential of libraries in providing information to professional information needs of library specialists and determine the prospects for further research related to improving the forms and methods of information service for this category of users.

scholarly journals What Can You Do with a Rock? Affordance Extraction via Word Embeddings

2017 ◽  
Author(s):  
Nancy Fulda ◽  
Daniel Ricks ◽  
Ben Murdoch ◽  
David Wingate
Keyword(s):  
Reinforcement Learning ◽  
Computational Complexity ◽  
Linear Algebra ◽  
Autonomous Agents ◽  
Common Knowledge ◽  
Search Space ◽  
Word Embeddings ◽  
Knowledge Database ◽  
Learning Agent ◽  
Action Spaces

Autonomous agents must often detect affordances: the set of behaviors enabled by a situation. Affordance extraction is particularly helpful in domains with large action spaces, allowing the agent to prune its search space by avoiding futile behaviors. This paper presents a method for affordance extraction via word embeddings trained on a tagged Wikipedia corpus. The resulting word vectors are treated as a common knowledge database which can be queried using linear algebra. We apply this method to a reinforcement learning agent in a text-only environment and show that affordance-based action selection improves performance in most cases. Our method increases the computational complexity of each learning step but significantly reduces the total number of steps needed. In addition, the agent's action selections begin to resemble those a human would choose.

scholarly journals On the issue of the formation and development of science as a social institution

2021 ◽  
pp. 207-213
Author(s):  
E. S. Nesterenko
Keyword(s):  
Russian Federation ◽  
Institutional Environment ◽  
Rapid Development ◽  
Social Institution ◽  
Scientific Activity ◽  
Human Potential ◽  
The Russian Federation ◽  
The Individual ◽  
Developing System ◽  
Comprehensive Study

The relevance of scientific research on the specifics of the institutional environment for the development of the Institute of Science in the Russian Federation is associated with the rapid development of the digital economy, in which the development of science is becoming the most important factor in ensuring Russia's competitiveness on the world stage. The author conducted a comprehensive study of the specifics of the institutional environment of the development of the Institute of Science in the Russian Federation. The article studies the stages of formation and development of science as a certain social institution. The paper presents the criteria of institutionalization and it is established that the Institute of Science meets them. The study highlights the purpose and functions of science as a social institution. The paper also proposes the institutional environment for the functioning of the Institute of Science, taking into account the state and the individual as an integral part of successful development. The author concludes that science as a social institution is a self-organizing, self-regulating and self-developing system based on the realization of human potential through special tools of scientific activity and special organizations and aimed at the production and dissemination of scientific knowledge.

scholarly journals PIQA: Reasoning about Physical Commonsense in Natural Language

2020 ◽  
Vol 34 (05) ◽  
pp. 7432-7439
Author(s):  
Yonatan Bisk ◽  
Rowan Zellers ◽  
Ronan Le bras ◽  
Jianfeng Gao ◽  
Yejin Choi
Keyword(s):  
Natural Language ◽  
Question Answering ◽  
Natural Language Understanding ◽  
Physical World ◽  
Future Research ◽  
Physical Interaction ◽  
Commonsense Reasoning ◽  
Cotton Swab ◽  
Language Understanding ◽  
Abstract Domains

To apply eyeshadow without a brush, should I use a cotton swab or a toothpick? Questions requiring this kind of physical commonsense pose a challenge to today's natural language understanding systems. While recent pretrained models (such as BERT) have made progress on question answering over more abstract domains – such as news articles and encyclopedia entries, where text is plentiful – in more physical domains, text is inherently limited due to reporting bias. Can AI systems learn to reliably answer physical commonsense questions without experiencing the physical world?In this paper, we introduce the task of physical commonsense reasoning and a corresponding benchmark dataset Physical Interaction: Question Answering or PIQA. Though humans find the dataset easy (95% accuracy), large pretrained models struggle (∼75%). We provide analysis about the dimensions of knowledge that existing models lack, which offers significant opportunities for future research.

Simplifying the Design of Human-Like Behaviour

2012 ◽  
pp. 32-53
Author(s):  
Joanna J. Bryson ◽  
Emmanuel Tanguy
Keyword(s):  
Autonomous Agents ◽  
Emotional Responses ◽  
Human Intelligence ◽  
Full Time ◽  
Emotional States ◽  
Virtual Character ◽  
Specific Instance ◽  
Emotion Representation ◽  
Representational Framework ◽  
Over Time

Human intelligence requires decades of full-time training before it can be reliably utilised in modern economies. In contrast, AI agents must be made reliable but interesting in relatively short order. Realistic emotion representations are one way to ensure that even relatively simple specifications of agent behaviour will be expressed with engaging variation, and those social and temporal contexts can be tracked and responded to appropriately. We describe a representation system for maintaining an interacting set of durative states to replicate emotional control. Our model, the Dynamic Emotion Representation (DER), integrates emotional responses and keeps track of emotion intensities changing over time. The developer can specify an interacting network of emotional states with appropriate onsets, sustains and decays. The levels of these states can be used as input for action selection, including emotional expression. We present both a general representational framework and a specific instance of a DER network constructed for a virtual character. The character’s DER uses three types of emotional state as classified by duration timescales, keeping with current emotional theory. We demonstrate the system with a virtual actor. We also demonstrate how even a simplified version of this representation can improve goal arbitration in autonomous agents.

Professional Information Needs of Library Specialists in Russia

2021 ◽  
Vol 70 (1) ◽  
pp. 7-20
Author(s):  
Marina Y. Neshcheret
Keyword(s):  
Information Needs ◽  
Rapid Development ◽  
Information Service ◽  
Library Science ◽  
Information Process ◽  
Cultural Workers ◽  
Use Of Resources ◽  
The Creation ◽  
Professional Information ◽  
Comprehensive Study

The article is devoted to the comprehensive study of the professional information needs (IN) of specialists of the central libraries of the subjects of the Russian Federation. The rapid development of high technologies in the field of accumulation, transmission and processing of information, the creation of modern telecommunications systems have led to the emergence of fundamentally new opportunities for organizing the information process. This, in turn, led to the qualitative growth of IN specialists, including those employed in the field of library activities. The specific features of IN library specialists are determined by their place and role in the modern process of cultural activity, industry orientation, nature of work and specialization. During 2018—2019, the Centre for Research of Problems of the Development of Libraries in the Information Society of the Russian State Library carried out research aimed at comprehensive study of the information needs of cultural workers employed in the library sphere. At the first stage of the research, there was comprehended the existing experience of studying professional information needs in the national library science. At the second stage, using the method of questionnaire survey, information needs of library specialists were studied in order to identify the most rational forms and methods of providing them. The analysis of the survey results made it possible to identify the sources of professional information, to reveal information resources that have the greatest importance and characterize specific features of librarians’ information needs.The author concludes on the need to expand the access to full-text databases and electronic versions of periodicals for library staff. The creation of integrated information centre could help providing library professionals with professional information. Currently, the function of such a centre is performed by the National Electronic Library, which includes the professional section for library specialists. The results of the study form theoretical and methodological basis for the rational use of resources and potential of libraries in providing information to professional information needs of library specialists and determine the prospects for further research related to improving the forms and methods of information service for this category of users.

Simulation Analysis of Mind Sports Games Based on Artificial Intelligence

2014 ◽  
Vol 989-994 ◽  
pp. 2065-2069 ◽  
Author(s):  
Guo Wen Cui ◽  
Xin Qiang Li
Keyword(s):  
Artificial Intelligence ◽  
Main Part ◽  
Simulation Analysis ◽  
Rapid Development ◽  
Coupling Model ◽  
Human Intelligence ◽  
Reduction Mechanism ◽  
Development Level ◽  
History Of ◽  
Development Mechanism

Mind sports games is rose in recent years, which is the comprehensive sports event taking the chess sports as the main part, and it is a perfect combination of human intelligence and sports art. Due to a simple history of mind sports games, there exists some problems that are the imbalance of development, lack of funds, and event organization difficulty, which has restricted the rapid development of mind sports games. Aiming at the problems of mind sports games encountering in the development, the paper first proposes the coupling development mechanism for the organization of mind sports games and its development mechanism, and then establishes the model of development mechanism based on the coupling reduction mechanism, and the model has been made simulation analysis. At last, the results show that the application of this coupling model can find the bottleneck of the development of mind sports games, so as to open the breakthrough point for its development, and to improve its development level.

scholarly journals NLog-like Inference and Commonsense Reasoning

2014 ◽  
Vol 9 ◽  
Author(s):  
Lenhart Schubert
Keyword(s):  
Knowledge Acquisition ◽  
Ordinary Language ◽  
World Knowledge ◽  
Commonsense Reasoning ◽  
Lexical Knowledge ◽  
Language Understanding ◽  
Natural Logic ◽  
Episodic Logic

Recent implementations of Natural Logic (NLog) have shown that NLog provides a quite direct means of going from sentences in ordinary language to many of the obvious entailments of those sentences. We show here that Episodic Logic (EL) and its Epilog implementation are well-adapted to capturing NLog-like inferences, but beyond that, also support inferences that require a combination of lexical knowledge and world knowledge. However, broad language understanding and commonsense reasoning are still thwarted by the “knowledge acquisition bottleneck”, and we summarize some of our ongoing and contemplated attacks on that persistent difficulty.

scholarly journals A Lexical Knowledge Representation Model for Natural Language Understanding

2009 ◽  
Vol 1 (4) ◽  
pp. 17-35 ◽  
Author(s):  
Ping Chen ◽  
Wei Ding ◽  
Chengmin Ding
Keyword(s):  
Knowledge Representation ◽  
Natural Language ◽  
Language Processing ◽  
Large Scale ◽  
Natural Language Understanding ◽  
Commonsense Reasoning ◽  
Lexical Knowledge ◽  
Language Understanding ◽  
Representation Model ◽  
Intelligent Information

Knowledge representation is essential for semantics modeling and intelligent information processing. For decades researchers have proposed many knowledge representation techniques. However, it is a daunting problem how to capture deep semantic information effectively and support the construction of a large-scale knowledge base efficiently. This article describes a new knowledge representation model, SenseNet, which provides semantic support for commonsense reasoning and natural language processing. SenseNet is formalized with a Hidden Markov Model. An inference algorithm is proposed to simulate human-like natural language understanding procedure. A new measurement, confidence, is introduced to facilitate the natural language understanding. The authors present a detailed case study of applying SenseNet to retrieving compensation information from company proxy filings.

scholarly journals A Lexical Knowledge Representation Model for Natural Language Understanding

2012 ◽  
pp. 193-210
Author(s):  
Ping Chen ◽  
Wei Ding ◽  
Chengmin Ding
Keyword(s):  
Knowledge Representation ◽  
Natural Language ◽  
Language Processing ◽  
Large Scale ◽  
Natural Language Understanding ◽  
Commonsense Reasoning ◽  
Language Understanding ◽  
Representation Model ◽  
Intelligent Information ◽  
Representation Techniques

Knowledge representation is essential for semantics modeling and intelligent information processing. For decades researchers have proposed many knowledge representation techniques. However, it is a daunting problem how to capture deep semantic information effectively and support the construction of a large-scale knowledge base efficiently. This paper describes a new knowledge representation model, SenseNet, which provides semantic support for commonsense reasoning and natural language processing. SenseNet is formalized with a Hidden Markov Model. An inference algorithm is proposed to simulate human-like natural language understanding procedure. A new measurement, confidence, is introduced to facilitate the natural language understanding. The authors present a detailed case study of applying SenseNet to retrieving compensation information from company proxy filings.

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