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Transcript
Forgetful and Emotional:
Recent Progress in Development of
Dynamic Memory Management System
for Conversational Agents
Michal Ptaszynski, Pawel Dybala,
Rafal Rzepka, Kenji Araki
Introduction
• Who Are We?
Kenji
Araki
Hokkaido University
Sapporo, Japan
…
Language Media Laboratory,
Graduate School of
Information Science and
Technology
Michal
Ptaszynski
Rafal
Rzepka
Pawel
Dybala
Introduction
• What Do We Do?
Genetic
Algorithms
Machine
Ethics
…
Affective
Computing
Humor
Processing
Introduction
• What Do We Do?
Genetic
Algorithms
Machine
Ethics
…
Affective
Computing
Humor
Processing
Problem Description
Problem Description
Problem Description
• Expanding Database
• of Dialogue Agent
• Becomes a Problem:
– Large space
– Processing time
– Which information is
good…?
– …At the certain time?
Problem Description
• How do humans do it?
– Agent Database =
Human Memory
• Memory:
– Process of Forgetting
(and Recalling)
Forgetting
• Definition: “Forgetting is a process in which
parts of knowledge become rearranged,
inaccessible or inactive.”[1,2]
• Usual attitude toward forgetting: BAD
• New findings:
– “forgetting is not a defect, but helps organize
memory and remember about important
things.” [8]
[1] J. R. Anderson, The Architecture of Cognition, Harvard University Press (1983).
[2] S. Markovitch and P. D. Scott. The Role of Forgetting in Learning, In Proceedings of The Fifth International Conference on Machine Learning. Ann Arbor, MI: Morgan Kaufmann, (1988).
[8] I. Kahn, N. M. Dudukovic, B. A. Kuhl and A. D. Wagner. Decreased demands on cognitive control reveal the neural processing benefits of forgetting, Nature Neuroscience, 10, pp. 908-914 (2007).
Forgetting
• Definition: “Forgetting is a process in which
parts of knowledge become rearranged,
inaccessible or inactive.”[1,2]
• Usual attitude toward forgetting: BAD
• New findings:
– “forgetting is not a defect, but helps organize
memory and remember about important
things.” [8]
[1] J. R. Anderson, The Architecture of Cognition, Harvard University Press (1983).
[2] S. Markovitch and P. D. Scott. The Role of Forgetting in Learning, In Proceedings of The Fifth International Conference on Machine Learning. Ann Arbor, MI: Morgan Kaufmann, (1988).
[8] I. Kahn, N. M. Dudukovic, B. A. Kuhl and A. D. Wagner. Decreased demands on cognitive control reveal the neural processing benefits of forgetting, Nature Neuroscience, 10, pp. 908-914 (2007).
Forgetting
• Forgetting is dependant on:
– Time (chronological fading of memories) [4]
– Emotions (Emotionally stronger memories fade
slower) [5,6,7]
• Recalling is indivisible
from Forgetting
[4] H. Ebbinghaus. Memory A Contribution to Experimental Psychology (1885). (translated by: T. Utsugi. Kioku nitsuite: jikken shinrigaku he no koken, Tokyo, Seishinsho Shobo (1978).
[5] F. G. Zitman. Emotion and memory in mood-anxiety disorders, Schreuder, BJN (2001).
[6] N. Luk. The Role of Emotions in Language Teaching, In The Journal of the Imagination in Language and Teaching, 7 (2002).
[7] P. Wolfe. The role of meaning and emotion in learning, In New Directions for Adult and Continuing Education, 2006(110), pp. 35-41 (2006).
Forgetting
• Forgetting is dependant on:
– Time (chronological fading of memories) [4]
– Emotions (Emotionally stronger memories fade
slower) [5,6,7]
The idea of chronological
• Recalling is indivisible
from Forgetting
forgetting has been applied in
AI and related fields [2,10]
(and at present is widely used:
e.g., access history in your
web browser).
[4] H. Ebbinghaus. Memory A Contribution to Experimental Psychology (1885). (translated by: T. Utsugi. Kioku nitsuite: jikken shinrigaku he no koken, Tokyo, Seishinsho Shobo (1978).
[5] F. G. Zitman. Emotion and memory in mood-anxiety disorders, Schreuder, BJN (2001).
[6] N. Luk. The Role of Emotions in Language Teaching, In The Journal of the Imagination in Language and Teaching, 7 (2002).
[7] P. Wolfe. The role of meaning and emotion in learning, In New Directions for Adult and Continuing Education, 2006(110), pp. 35-41 (2006).
[2] S. Markovitch and P. D. Scott. The Role of Forgetting in Learning, In Proceedings of The Fifth International Conference on Machine Learn-ng. Ann Arbor, MI: Morgan Kaufmann, (1988).
[10] M. Ishikawa. A Structural Connectionist Learning Algorithm with Forgetting, J. of Japanese Society for Artificial Intelligence 5(5) (1990).
Forgetting
• Forgetting is dependant on:
– Time (chronological fading of memories) [4]
– Emotions (Emotionally stronger memories fade
slower) [5,6,7]
The idea of chronological
• Recalling is indivisible
from Forgetting
forgetting has been applied in
AI and related fields [2,10]
(and at present is widely used:
e.g., access history in your
web browser).
However the ideas of applying emotional weights in
forgetting algorithms and adding the recalling ability
has not been studied sufficiently yet.
*) Although this might change in the near future
(see RWWA Symposium in the next room)
[4] H. Ebbinghaus. Memory A Contribution to Experimental Psychology (1885). (translated by: T. Utsugi. Kioku nitsuite: jikken shinrigaku he no koken, Tokyo, Seishinsho Shobo (1978).
[5] F. G. Zitman. Emotion and memory in mood-anxiety disorders, Schreuder, BJN (2001).
[6] N. Luk. The Role of Emotions in Language Teaching, In The Journal of the Imagination in Language and Teaching, 7 (2002).
[7] P. Wolfe. The role of meaning and emotion in learning, In New Directions for Adult and Continuing Education, 2006(110), pp. 35-41 (2006).
[2] S. Markovitch and P. D. Scott. The Role of Forgetting in Learning, In Proceedings of The Fifth International Conference on Machine Learn-ng. Ann Arbor, MI: Morgan Kaufmann, (1988).
[10] M. Ishikawa. A Structural Connectionist Learning Algorithm with Forgetting, J. of Japanese Society for Artificial Intelligence 5(5) (1990).
System Description
• Dialogue Agent is trained on conversation sets
System Description
• Dialogue Agent is trained on conversation sets
• Each conversation set is one “context unit” (CU)
CU_01
CU_02
CU_03
A:すまん。俺も裏ぐった。 文才が無いか
ら、過程は書けないけど。 このスレま
じで魔力ありすぎ… おまいらにも光あ
れ…
B: なんだとこあんちくしょうぁあああああ
A:きになる
A:帰還しますた とりあえず着替えてきます(・∀・)
B:電車 キタ━━━(゚∀゚)━━━!!!!!
A:今戻りました。
結果から報告すると成功でうぇdrftgyふじこl
B:>>731 彼女が出来たのか?
A:>>734 違うけど。でも大チャンス。こういう
こと続くとネタにしか聞こえないよな。とに
かくおまいら外に出てみろ
思い出しながら経過など報告させて頂きます。
それとみんな有難う。
B:性交キタキタキタキタ━━━(゚∀゚≡(゚∀゚≡゚∀゚)≡゚∀゚)━━━━!!!!!!!!!!
A:こんにちは
B:さよなら
(different topics  different words used)
System Description
• Dialogue Agent is trained on conversation sets
• Each conversation set is one “context unit” (CU)
• Agent database contains many CUs
System Description
•
•
•
•
Dialogue Agent is trained on conversation sets
Each conversation set is one “context unit” (CU)
Agent database contains many CUs
But not all of them have to be processed at all
times  Some of them could be deactivated
when not needed (forgetting)
System Description
•
•
•
•
Dialogue Agent is trained on conversation sets
Each conversation set is one “context unit” (CU)
Agent database contains many CUs
But not all of them have to be processed at all
times  Some of them could be deactivated
when not needed (forgetting) and reactivated
again when needed (recalling)
System Description
Need to answer these questions:
1. On what basis agent should forget a CU?
2. What information could be extracted from a
CU to fulfill this task?
3. How to recall a deactivated CU?
System Description
1. On what basis agent should forget a CU?
Forgetting is a function of
Time (T) and Emotional value (E): V = f(T, E)
System Description
2. What information could be extracted from a
CU to fulfill this task?
Every CU has:
attached when created and
- a certain time stamp
renewed when information
from a CU is used in other
conversation
- a certain emotional level
need to
measure it
System Description
Measuring emotional level of a CU:
- Perform affect analysis [16] of all utterances in
the training set to obtain emotive values.
- Approximation of all emotive values =
emotional level of the conversation (CU).
- (perform continuously also on new CUs)
[16] M. Ptaszynski, P. Dybala, R. Rzepka and K. Araki. Affecting Corpora: Experiments with Automatic Affect Annotation System - A Case Study of the 2channel
Forum -, In Proceedings of The Conference of the Pacific Association for Computational Linguistics 2009 (PACLING-09), pp. 223-228 (2009).
System Description
• Forgetting process:
Time
Emotions
• Recalling
“Forget” by zipping parts of database
and storing them using less space
System Description
Use DB in
conversation
DB
• Recalling
DBを会話で利用
Unzip and reactivate
the relevant CUs
Reactivate
similar CU
CUをDBに追加
CU
User
input
ユーザと会話
Calculate similarity
with deactivated CUs
CU
Extract association lists
from Internet [24]
Internet
インターネット
[24] S. Higuchi, R. Rzepka and K. Araki. A Casual
Conversation System Using Modality and Word
Associations Retrieved from the Web, In Proceedings
of the EMNLP-2008, pp. 382-390 (2008).
System Description
Forgetting process:
Time
Emotions
Recalling
Problem Description
• Expanding Database
• of Dialogue Agent
• Becomes a Problem:
– Large space
– Processing time
– Which information is
good…?
– …At the certain time?
Problem Description
• Expanding Database
• of Dialogue Agent
• Becomes a Problem:
Large space
Processing time
– Which information is
good…?
– …At the certain time?
Problem Description
• Expanding Database
• of Dialogue Agent
• Becomes a Problem:
Large space
Processing time
– Which information is
good…?
– …At the certain time?
System Description
• Construction of a CU
System Description
• Construction of a CU
① - T. Kudo. MeCab: Yet Another Part-of-Speech and Morphological Analyzer, 2001. http://mecab.sourceforge.net/
② - T. Kudo, Y. Matsumoto. Japanese Dependency Analyisis using Cascaded Chunking, CONLL 2002, Taipei (2002).
③ - M. Ptaszynski, P. Dybala, R. Rzepka and K. Araki. Affecting Corpora: Experiments with Automatic Affect Annotation System - A Case Study of the 2channel
Forum -, In Proceedings of The Conference of the Pacific Association for Computational Linguistics 2009 (PACLING-09), pp. 223-228 (2009).
- Michal Ptaszynski, Jacek Maciejewski, Pawel Dybala, Rafal Rzepka, Kenji Araki, "CAO: Fully Automatic Emoticon Analysis System", In Proceedings of The
Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI-10), Atlanta, USA, to appear in July, 2010
④ - M. Ptaszynski, P. Dybala, W. Shi, R. Rzepka and K. Araki. Towards Context Aware Emotional Intelligence in Machines: Computing Contextual
Appropriateness of Affective States, In Proceedings of Twenty-first International Joint Conference on Artificial Intelligence (IJCAI-09), Pasadena, California,
USA, pp. 1469-1474 (2009).
Conclusions
• We presented the description of a dynamic
database management system for dialogue
agents.
• The system borrows from memory processes
in humans: forgetting and recalling, based
on:
– Chronological fading of memories (CUs)
– Emotional values attached to memories (CUs)
• We have developed sub-systems to
implement the method
Further Work
• Implementation
• Evaluation
Thank you for your attention!