BibTeX Entry

@UNPUBLISHED{Makino:1996:Zj, author = {牧野 貴樹 and 丹羽 容輔 and 長井 歩}, title = {{AP}-1000+ による高速フーリエ変換の実装}, note = {並列処理シンポジウム主催 第3回並列処理ソフトウェアコンテスト優勝者 (早稲田大学国際会議場にて口頭発表)}, year = 1996, month = JUN }

@MISC{Makino:1997a:Dj, author = {牧野 貴樹}, title = {高速な素性構造抽象機械の実現}, howpublished = {卒業論文、東京大学理学部情報科学科}, year = 1997, note = {(英語)}, ps = {makino1997a.ps.gz}, abstract = {本研究では Carpenter らにより基本的骨格が提案された素性構造抽象機械につ いて述べる。自然言語処理や、人工知能などの分野で使用される素性構造は、 従来は Prolog 等の論理型言語で、言語に組み込みの単一化ルーチン を使用して処理されることが一般的であった。素性構造抽象機械では、素性構造 をあらかじめ単一化手順として抽象機械の命令列に変換しておくことで、単一化 を、抽象機械上の命令実行という効率の高い形で行うことができる。本研究では、 実際に実装した素性構造抽象機械に対して命令セットやコンパイル方法の拡張を 行い、より高い効率を追求した。また、他の実装系とのパフォーマンスの比較も 行った。} }

@INPROCEEDINGS{Makino:1997b:Qj, title = {素性構造抽象機械と部分的単一化の実現}, author = {牧野 貴樹 and 西田 健二 and 鳥澤 健太郎 and 辻井 潤一}, year = 1997, booktitle = {言語処理学会第3回年次大会発表論文集}, pages = {193$\,$--$\,$196}, address = {京都市}, pdf = {makino1997b.pdf} }

@INPROCEEDINGS{Makino:1997c:O, author = {Takaki Makino and Kentaro Torisawa and {Jun-ichi} Tsujii}, title = {{LiLFeS} --- Practical Programming Language For Typed Feature Structures}, pages = {239$\,$--$\,$244}, booktitle = {Proceedings of the 4th {N}atural {L}anguage {P}rocessing {P}acific {Rim} {S}ymposium}, year = 1997, address = {Phuket, Thailand}, ps = {makino1997c.ps.gz}, abstract = {This paper describes LiLFeS, an integrated unification-based programming system for linguistic formalisms based on typed feature structures, such as HPSG. The core engine of LiLFeS is an abstract machine developed for efficient handling of typed feature structures. Its basic design and optimization techniques are described. Performance comparisons between LiLFeS and other systems for typed feature structures show that LiLFeS is more than 50 times faster than ALE, and competitive to ProFIT.} }

@INPROCEEDINGS{Nishida:1997:O, author = {Nishida, Kenji and Makino, Takaki and Torisawa, Kentaro and Tateisi, Yuka and Tsujii, {Jun-ichi}}, title = {Extension of a Feature Structure Abstract Machine for Partial Unification}, booktitle = {Proceedings of the Conference of {P}acific {A}ssociation for {C}omputational {L}inguistics ({PACLING} '97)}, pages = {232$\,$--$\,$243}, year = 1997, address = {Ohme, Japan}, ps = {nishida97.ps.gz}, abstract = { This paper describes an extension of a feature structure abstract machine for supporting partial unification, which is used in an efficient parsing algorithm for HPSG proposed by Torisawa et al. An abstract machine for attribute-value logics, a framework for processing typed feature structures proposed by Carpenter and Qu, is not only efficient but also easily extendable. We extended the abstract machine for partial unification by only adding a set of instructions to the machine. By combining this technique with the pre-computation of possible feature structures, efficiency of HPSG parsing is improved. We also show the feasibility of our implementation by a series of experiments. } }

@INPROCEEDINGS{Tateisi:1997:Sj, author = {建石 由佳 and 鳥澤 健太郎 and 牧野 貴樹 and 西田 健二 and 渕上 正睦 and 辻井 潤一}, title = {{LTAG} 文法からの変換による {HPSG} 英文法の生成}, booktitle = {情報処理学会 自然言語処理研究会 研究報告 NL-122}, pages = {119$\,$--$\,$126}, year = 1997, ps = {tateisi1997.ps.gz} }

@INPROCEEDINGS{Makino:1998:Ox, title = {{LiLFeS} --- Towards a Practical {HPSG} Parser}, author = {Takaki Makino and Minoru Yoshida and Kentaro Torisawa and {Jun-ichi} Tsujii}, year = 1998, booktitle = {Proceedings of the 17th {I}nternational {C}onference on {C}omputational {L}inguistics and the 36th {A}nnual {M}eeting of the {A}ssociation for {C}omputational {L}inguistics}, pages = {807$\,$--$\,$811}, address = {Montreal, Canada}, ps = {makino1998.ps.gz}, abstract = {This paper presents the LiLFeS system, an efficient feature-structure description language for HPSG. The core engine of LiLFeS is an Abstract Machine for Attribute-Value Logics, proposed by Carpenter and Qu. Basic design policies, the current status, and performance evaluation of the LiLFeS system are described. The paper discusses two implementations of the LiLFeS. The first one is based on an emulator of the abstract machine, while the second one uses a native-code compiler and therefore is much more efficient than the first one.} }

@INPROCEEDINGS{Yoshida:1998:Sj, author = {吉田 稔 and 牧野 貴樹 and 鳥澤 健太郎 and 辻井 潤一}, title = {素性構造処理言語 {LiLFeS} の最適化技術}, booktitle = {言語処理学会第4回年次大会発表論文集}, year = {1998}, address = {福岡市}, pages = {93$\,$--$\,$96} }

@INPROCEEDINGS{Torisawa:1999:S, author = {Kentaro Torisawa and Takaki Makino and Minoru Yoshida and Takashi Ninomiya and Kenji Nishida and Hideo Imai and Yutaka Mitsuishi and Hiroshi Kanayama and Yuka Tateisi and Yusuke Miyao and {Jun-ichi} Tsujii}, year = 1999, title = {Practical {HPSG} Parsers.}, booktitle = {Proceedings of {JSPS} Annual Symposium on Intelligent Information and Advanced Information Processing}, pages = {46$\,$--$\,$50}, ps = {jsps99-hpsg.ps.gz} }

@INPROCEEDINGS{Kazama:1999:Sj, author = {風間 淳一 and 光石 豊 and 牧野 貴樹 and 鳥澤 健太郎 and 松田 晃一 and 辻井 潤一}, title = {チャットのための日本語形態素解析}, booktitle = {言語処理学会第5回年次大会発表論文集}, year = {1999}, address = {東京都}, pages = {509$\,$--$\,$512}, ps = {kazama_nlp99.ps.gz}, pdf = {kazama_nlp99.pdf} }

@INPROCEEDINGS{Sadamasa:1999:Sj, author = {定政 邦彦 and 牧野 貴樹 and 光石 豊 and 鳥澤 健太郎 and 松田 晃一 and 辻井 潤一}, title = {「パーソナルエージェント用自然言語インターフェース」開発ツールキット ({PANLI} toolkit)}, booktitle = {言語処理学会第5回年次大会発表論文集}, year = {1999}, address = {東京都}, pages = {393$\,$--$\,$396} }

@MASTERSTHESIS{Makino:1999:Dj, author = {牧野 貴樹}, title = {型付き素性構造を使用する単一化ベースのプログラミング言語のためのネイティブコードコンパイラ}, school = {東京大学 大学院理学系研究科 情報科学専攻}, type = {修士論文}, address = {東京}, year = 1999, note = {(英語)}, ps = {makino1999.ps.gz}, abstract = { 本論文は、型付き素性構造 (TFS) を使用する単一化ベースのプログラミング言語 LiLFeSのためのネイティブコードコンパイラの設計と実装について述べる。素性 構造を使用するフォーマリズム上で自然言語処理を行うための基幹言語として、 Carpenterらの提案する属性値論理抽象機械 (AMAVL)を元に設計された LiLFeS で あるが、大量のコーパスからの統計学習などを含めた高度な自然言語処理を実現 するには処理能力の点で不十分であった。LiLFeSの実装に応用ができる高効率な Prologの実装方式としては、PrologのネイティブコードコンパイラAquarius Prolog などさまざまな研究が行われてきている。しかし、素性構造の単一化効 率を高めるには、型情報を利用した最適化を実現することが必要で、そのために は型操作を含む単一化コードをコンパイラが直接出力しなければならない。これ は、既存のProlog実装の単純な拡張や、AMAVLとの統合だけでは実現することがで きなかった。本論文では、Aquarius Prologの実装方式であるBerkeley Abstract Machineを拡張した、LiLFeSネイティブコードコンパイラの設計について述べる。 具体的には、抽象機械上での型付き素性構造の単一化の実現手法に関して、 (1) 型操作を含むコードを出力に含めるための単一化アルゴリズムの構築と分析、(2) それらのアルゴリズムを記述するための抽象機械命令の設計、(3) その上でコー ド最適化のための文脈情報を提供する型階層および確定節プログラムの静的解析 技術、の3点の提案について詳述する。また、他のLiLFeSおよびProlog処理系との 性能比較によって、本論文で提案する実装が高効率であることを示す。 } }

@INPROCEEDINGS{Yoshida:1999:S, author = {Yoshida, Minoru and Takashi Ninomiya and Kentaro Torisawa and Takaki Makino and {Jun'ichi} Tsujii}, year = 1999, title = {Efficient {FB-LTAG} Parser and its Parallelization}, booktitle = {Proceedings of the Pacific Association for Computational Linguistics (PACLING) '99}, address = {Waterloo, Canada}, pages = {90$\,$--$\,$103}, pdf = {http://www-tsujii.is.s.u-tokyo.ac.jp/%7Emino/pacling99.pdf} }

@ARTICLE{Miyao:2000:K, author = {Yusuke Miyao and Takaki Makino and Kentaro Torisawa and {Jun-ichi} Tsujii}, title = {The {LiLFeS} abstract machine and its evaluation with the {LinGO} grammar}, journal = {Natural Language Engineering}, editor = {Flickinger, Dan and Oepen, Stephan and Tsujii, {Jun-ichi} and Uszkoreit, Hans}, volume = 6, number = 1, note = {({S}pecial Issue on Efficient Processing with {HPSG})}, pages = {47$\,$--$\,$61}, year = 2000, ps = {miyao2000.ps.gz}, abstract = { This article evaluates the efficiency of the LiLFeS abstract machine by performing parsing tasks with the LinGO English resource grammar. The instruction set of the abstract machine is optimized for efficient processing of definite clause programs and typed feature structures. LiLFeS also supports various tools required for efficient parsing (e.g. efficient copying, a built-in CFG parser) and the constructions of standard Prolog (e.g. cut, assertions, negation as failure). Several parsers and large-scale grammars, including the LinGO grammar, have been implemented in or ported to LiLFeS. Precise empirical results with the LinGO grammar are provided to allow comparison with other systems. The experimental results demonstrate the efficiency of the LiLFeS abstract machine. } }

@INPROCEEDINGS{Makino:2001:O, author = {Makino, Takaki and Aihara, Kazuyuki and Tsujii, {Jun-ichi}}, year = {2001}, title = {Towards Sentence Understanding: Phase Arbitration in Temporal-Coding Memory Mechanism}, booktitle = {Proceedings of the Second Workshop on Natural Language Processing and Neural Networks (NLPNN'2001)}, pages = {46$\,$--$\,$52}, address = {Tokyo, Japan}, pdf = {makino2001.pdf}, abstract = {This paper explores a mechanism of memory in human brain from a viewpoint of sentence understanding. We pointed out the following: (1) Some complexity must be incorporated into memory coding in order to be capable of representing binding in a meaning of a sentence. (2) When temporal coding is used to achieve the complexity, some mechanism is required to arbitrate phases (temporal slots) among memorized items. (3) Considering its implementation, the mechanism is likely to be global, which resembles a sort of structured memory, such as a push-down stack. (4) Episodic memory, which is thought to be formed through mammal hippocampus, can be regarded as a phase arbitration mechanism and is possibly related in depth to sentence understanding. } }

@PHDTHESIS{Makino:2002a:Dxj, author = {牧野 貴樹}, title = {言語理解のためのパルス神経回路網 -- 短期記憶機構と文理解の離散イベント式シミュレーション}, school = {東京大学 大学院理学系研究科 情報科学専攻}, type = {博士論文}, address = {東京}, month = DEC, year = 2001, pdf = {makino2002a.pdf}, ps = {makino2002a.ps.gz}, note = {(英語)}, abstract = {人間の言語理解がどのようなアルゴリズムで実現されているかを調べるために、さまざまな言語処理アルゴリズムが研究されてきたが、生理学的証拠と結びつくものは見つかっていない。このような状況では、言語理解過程に関する計算理論からわかる言語理解メカニズムの実装上の制約や有利な構造を調べるというアプローチが有効である。\par 本論文では、言語理解に適した人間の短期記憶機構のモデルと、そのシミュレーションに必要な技術について提案する。具体的には、以下の３項目についての研究を行う。\par (1) 言語理解に適した短期記憶機構を神経回路網で構築するときに必要となる要素の探究 \par (2) 連続時間での高速かつ一般的なパルス神経回路網シミュレーション技術 \par (3) (1) 及び (2) を利用した、言語理解の原始的なシミュレーション \par ここで (1) については、言語を取り扱う神経回路網が備えているべき要素について、次のようなことを明らかにした。i) 言語理解の結果を表現するには束縛問題を解決することが必要であり、そのためには神経回路網の時間領域での振る舞いを利用することが最も有望であること。ii) 位相調停を実現するために、構造的な時系列記憶システムが構築されるべきであること。iii) 時系列予測の形式で文法規則の適用が実装できること。 \par また、(2) に関しては、イベント離散方式によるパルス神経回路網シミュレーション方式を研究した。位相調停など複雑な時間領域での操作を研究するために必要となる、時間精度の高い回路網シミュレーションは、時間離散方式による従来の手法ではシミュレーション速度に限界があった。一方、イベント離散方式には一般的なニューロンモデルに対し遅延発火が扱えないという問題があった。本研究で提案する二次漸進分割法は、遅延発火を解析的に計算することにより、一般的なニューロンモデルに対してもイベント離散方式でパルス回路網シミュレーションが構築できることを示す。また、冗長な遅延発火計算を検出することで遅延発火の処理を高速化する手法についても述べる。 \par そして、(3) においては、(1) 及び (2) の研究を例証するために、３〜４単語程度の単純な文を理解する神経回路網シミュレーションを構築する。ここで構築した言語理解システムをさまざまな側面から検討し、よりよい文の理解のために研究すべき方向について考察する。\par } }

@INPROCEEDINGS{jun3:2002b:S, author = {Araki, Junko and Takashi Ninomiya and Takaki Makino and {Jun'ichi} Tsujii}, title = {Action Vectors for Interpreting Route Descriptions}, booktitle = {Proceedings of the AAAI-02 Workshop on Spatial and Tempolal Reasoning}, ps = {http://www-tsujii.is.s.u-tokyo.ac.jp/papers/jun3-aaai2002workshop.ps}, year = {2002} }

@INPROCEEDINGS{jun3:2002c:S, author = {Araki, Junko and Takashi Ninomiya and Takaki Makino and {Jun'ichi} Tsujii}, title = {Two Perspective systems Using a Route as a Reference Object}, booktitle = {Proceedings of the sixth World Multiconference on Systemics, Cybernetics and Informatics ({SCI} 2002)}, ps = {http://www-tsujii.is.s.u-tokyo.ac.jp/papers/jun3-sci2002.ps}, year = {2002} }

@INPROCEEDINGS{kazama:2002a:S, author = {Kazama, {Jun'ichi} and Takaki Makino and Yoshihiro Ohta and {Jun'ichi} Tsujii}, title = {Tuning Support Vector Machines for Biomedical Named Entity Recognition}, booktitle = {Proceedings of the Natural Language Processing in the Biomedical Domain (ACL 2002)}, year = {2002}, month = {July}, address = {Philadelphia, PA, USA}, ps = {http://www-tsujii.is.s.u-tokyo.ac.jp/%7Ekazama/papers/kazama_aclbio02.ps}, pdf = {http://www-tsujii.is.s.u-tokyo.ac.jp/%7Ekazama/papers/kazama_aclbio02.pdf} }

@INPROCEEDINGS{Ninomiya:2002:S, author = {Ninomiya, Takashi and Makino, Takaki and Tsujii, Jun'ichi}, year = 2002, month = OCT, title = {An Indexing Scheme for Typed Feature Structures}, booktitle = {Proceedings of the 19th {I}nternational {C}onference on {C}omputational {L}inguistics}, address = {Taipei, Taiwan}, ps = {coling2002-ninomi-b.ps.gz}, pdf = {coling2002-ninomi-b.pdf}, abstract = {This paper describes an indexing substrate for typed feature structures (ISTFS), which is an efficient retrieval engine for typed feature structures. Given a set of typed feature structures, the ISTFS efficiently retrieves its subset whose elements are unifiable or in a subsumption relation with a query feature structure. The efficiency of the ISTFS is achieved by calculating a unifiability checking table prior to retrieval and finding the best index paths dynamically.} }

@INPROCEEDINGS{Makino:2002c:Rj, author = {牧野 貴樹 and 合原 一幸}, year = 2002, month = SEP, title = {言語理解の計算理論が神経回路網モデル開発に及ぼす影響}, booktitle = {日本神経回路学会 第12回全国大会 講演論文概要集}, address = {鳥取県鳥取市}, pdf = {jnns2002.pdf}, abstract = {}, note = {2002年日本神経回路学会奨励賞受賞} }

@INCOLLECTION{Makino:2003e:Cx, author = {Takaki Makino and Yusuke Miyao and Kentaro Torisawa and {Jun-ichi} Tsujii}, title = {Native-Code Compilation of Feature Structures}, booktitle = {Collaborative Language Engineering: A Case Study in Efficient Grammar-based Processing}, publisher = {{CSLI} Publications}, address = {Stanford, {CA}}, editor = {Oepen, Stephan and Flickinger, Dan and Tsujii, {Jun-ichi} and Uszkoreit, Hans}, year = 2003, pdf = {makino2000.pdf}, ps = {makino2000.ps.gz} }

@MISC{Makino:2003c:Rj, author = {牧野 貴樹 and 合原 一幸}, title = {時間の流れと「ことば」に関する脳の処理の仮説}, year = 2003, month = JAN, note = {第3回 脳と心のメカニズム 冬のワークショップ (北海道ルスツ) においてポスター発表}, abstract = {} }

@MISC{Makino:2003d:Rj, author = {牧野 貴樹 and 合原 一幸}, title = {時間依存神経可塑性で構成される自己組織化マップ}, year = 2003, month = AUG, note = {第4回 脳と心のメカニズム 夏のワークショップ (新潟県湯沢町) においてポスター発表}, pdf = {poster2003.pdf}, abstract = {} }

@ARTICLE{Makino:2003a:Jx, author = {Takaki Makino}, title = {A Discrete-Event Neural Network Simulator for General Neuron Models}, journal = {Neural Computing \& Applications}, year = 2003, volume = 11, pages = {210--223}, pdf = {nca2003.pdf}, publisher = {Springer-Verlag London}, abstract = {Efficient simulation techniques for a discrete-event pulsed neural network simulator were developed. In a discrete-event simulation framework, simulation of complex neural behaviors, such as phase precession and phase arbitration, demands prediction of delayed firing times. The new technique, the incremental partitioning method, uses linear envelopes of the state variable of a neuron to partition the simulated time so that the delayed-firing time is reliably calculated by applying the bisection-combined Newton-Raphson method to every partition. The quick filtering technique is also proposed for reducing calculation cost of linear envelopes. The developed simulator, \textsc{Punnets}, has achieved efficiency and precision but still is capable of simulating a complex behavior of large-scale neural network models.} }

@TECHREPORT{Makino:2003b:Txj, title = {Self-observation Principle for Estimating the Other's Internal State -- A New Computational Theory of Communication}, author = {Takaki Makino and Kazuyuki Aihara}, type = {Mathematical Engineering Technical Reports}, institution = {Department of Mathematical Informatics, Graduate School of Information Science and Technology, the University of Tokyo}, number = {METR 2003--36}, year = 2003, month = OCT, pdf = {METR03-36.pdf}, note = {\url{METR03-36.pdf}{提出版 (.pdf)}のほかに\url{METR03-36e.pdf}{ネイティブチェック反映版 (.pdf)}、\url{METR03-36j.pdf}{非公式日本語版 (.pdf)}もあります}, abstract = {人間のような高度なコミュニケーションの基礎と考えられる、自己と同等な他者の内部状態推定に関する計算理論を提案する。他者の内部状態推定においては、推定者のパラメータ次元の制約、主観的情報と客観的情報の相互変換という2つの本質的な困難が存在する。我々が提案する自己観測原理は、自己観測での学習に基づいて、この2つの問題を同時に解決する。すなわち、獲得が容易な自己のダイナミクスを学習することで他者のダイナミクスに関する先行知識を得られるので、パラメータ次元の制約を緩和できる。また、自己の主観的状態と自己を客観的に観測した情報の関連付けを学習することで、他者を客観的に観測した情報と他者にとっての主観的情報の相互変換を可能にする。本論文では、力学系観測問題の枠組でコミュニケーション問題を定式化し、そのうえで2つの困難とその解決法について論じる。また、進化心理学・神経科学との関連についても考察する。} }

@INPROCEEDINGS{Makino:2004a:O, author = {Makino, Takaki and Aihara, Kazuyuki}, year = 2004, month = MAR, title = {Self-observation Principle for Estimating Peers' Internal State -- New Computational Theory on Communication}, booktitle = {Proceedings of the 2nd internal symposium on emergent mechanism of communication in the brain}, address = {Awaji-shima, Hyogo}, pdf = {makino2004awaji.pdf} }

@INPROCEEDINGS{Makino:2004b:O, author = {Makino, Takaki and Jianfeng Feng}, year = 2004, month = NOV, title = {Configuring Spiking Neural Networks for Given Spatio-Temporal Patterns}, booktitle = {Proceedings of 2004 International Workshop on Biologically Inspired Computing}, address = {Sendai, Miyagi} }

@MISC{Makino:2005b:Rj, author = {牧野 貴樹 and 合原 一幸}, title = {自己観測原理と繰り返し囚人のジレンマ}, year = 2005, month = JAN, note = {第5回 脳と心のメカニズム 冬のワークショップ (北海道ルスツ) においてポスター発表}, abstract = {} }

@ARTICLE{Makino:2005c:J, author = {Makino, Takaki and Hirayama, Kotaro and Aihara, Kazuyuki}, title = {Understanding others: Possible links among parity, mirror neurons, and communication}, year = 2005, note = {(Supplemental commentary to the article ``From monkey-like action recognition to human language: An evolutionary framework for neurolinguistics'' by Michael A. Arbib) http://www.bbsonline.org/Preprints/Arbib-05012002/Supplemental/}, journal = {Behavioral Brain \& Sciences}, abstract = {In the target article, LR3 (Parity), one of the possible criteria for language readiness, is defined with a simple description: ``What counts for the speaker (or producer) must count for the listener (or receiver).'' Based on a self-observation principle, we would like to suggest that this ability plays a much more crucial role in communication than can be inferred from the statement, namely, the role of ``understanding others.''} }

@MISC{Makino:2006a:J, author = {Makino, Takaki and Jianfeng Feng}, year = 2006, title = {Configuring Spiking Neural Networks for Given Spatio-Temporal Patterns}, note = {in submission to {\it IEEE Transactions on Neural Networks}.}, pdf = {makino2006configuring.pdf}, abstract = {We have developed a general framework to configure a spiking neuronal network so that it can precisely generate a desired spatio-temporal pattern of spikes. The unit of spiking neuronal networks employed here is a leaky integrate-and-fire model with a connection delay. We have shown that the required network configuration, and its existence, can be characterized by a set of linear inequalities constructed from the given pattern. The stability of the configured spiking neuronal network is discussed, which lead us to applying some routine methods in linear-programming to solve the set of inequalities, and yields the desirable spiking neural network configuration. To demonstrate the application of our approach, numerical examples with randomly generated patterns were explored and included.} }

@INPROCEEDINGS{Makino:2006b:P, author = {Makino, Takaki and Aihara, Kazuyuki}, year = 2006, title = {Multi-agent Reinforcement Learning Algorithm to Handle Beliefs of Other Agents' Policies and Embedded Beliefs}, booktitle = {Proceedings of the 5th International Joint Conference on Autonomus Agents and Multiagent Systems (AAMAS'06)}, pages = {789--791}, month = MAY, address = {Hakodate, Hokkaido}, pdf = {makino2006multiagent.pdf}, abstract = {We have developed a new series of multi-agent reinforcement learning algorithms that choose a policy based on beliefs about co-players’policies. The algorithms are applicable to situations where a state is fully observable by the agents, but there is no limit on the number of players. Some of the algorithms employ embedded beliefs to handle the cases that co-players are also choosing a policy based on their beliefs of others’ policies. Simulation experiments on Iterated Prisoners’ Dilemma games show that the algorithms using on policy-based belief converge to highly mutually-cooperative behavior, unlike the existing algorithms based on action-based belief.} }

@ARTICLE{Makino:2007a:Jxj, author = {牧野 貴樹 and 合原 一幸}, title = {他者理解をシミュレーションする}, journal = {シミュレーション}, volume = 26, number = 3, year = 2007, page = {171--175}, abstract = {We briefly describe \textit{mentalizing}, or understanding others' mental states, in an active research area of cognitive science. To overcome inaccessiblity of others' mental states, theoretical studies assume some mentalizing mechanism in the brain, including simulating others' behavior within knowledge of behavior of the self. We also present our computer-simulation study that tackles the role of mentalizing in a social environment, which examines behavior of agents based on reinforcement learning in Iterated Prisoners' Dilemma games. The results show that agents that choose actions using the estimated policy (corresponding to the mental state) of the co-player, achieve higher cooperation rates than control agents do, which choose actions using only the expected action of the co-player, or only the recent history of game plays. } }

@ARTICLE{Makino:2008a:Jx, author = {Makino, Takaki}, title = {Failure, instead of inhibition, should be monitored for the distinction of self/other and actual/possible actions}, journal = {Behavioral and Brain Sciences}, year = 2008, volume = 31, number = 1, pages = {32--33}, publisher = {Cambridge University Press}, address = {New York, NY, USA}, note = {A commentary for Susan Hurley's article ``The Shared Circuits Model: How Control, Mirroring and Simulation Can Enable Imitation, Deliberation, and Mindreading''.}, abstract = {I suggest that layer 4 of the shared circuits model (SCM) should monitor the failure of performing an action, instead of output inhibition, to obtain actual/possible and self/other distinction. The target article's assumption of selective inhibition leaves some questions unansweres, such asa the criteria for the selection. Monitoing failure can answer these questions because failure does not require selection. It also provices a basis for more likely explanation for the phylogenetic and ontogenetic origin of both monitoring and output inhibition.} }

@INPROCEEDINGS{Makino:2008b:Qj, author = {牧野 貴樹 and 高橋 泰城 and 福井 裕輝}, title = {サイコパス傾向と脳内意思決定メカニズム：強化学習理論を用いた記述}, booktitle = {第4回 日本司法精神医学会大会}, year = {2008}, month = MAY }

@INPROCEEDINGS{Mino:2008a:Qj, author = {美濃 由紀子 and 岡田 幸之 and 菊池 安希子 and 牧野 貴樹 and 吉川 和男}, title = {医療観察法制度の通院医療における精神保健福祉法入院の併用実態と課題 〜指定通院医療機関のモニタリング調査から〜}, booktitle = {第4回 日本司法精神医学会大会}, year = {2008}, month = MAY }

@INPROCEEDINGS{Makino:2008c:Qj, author = {牧野 貴樹}, title = {{POMDP} 環境中での{TD}-Networkの自動獲得: 単純再帰構造による拡張}, booktitle = {第22回 人工知能学会全国大会 予稿集}, year = {2008}, month = JUN, note = {to appear} }

@INPROCEEDINGS{Makino:2008d:Qj, author = {牧野 貴樹 and 合原 一幸}, title = {自己観測原理: 他者認知の数理的枠組}, booktitle = {第22回 人工知能学会全国大会 予稿集}, year = {2008}, month = JUN, note = {to appear}, abstract = {We briefly describe \textit{mentalizing}, or understanding others' mental states, in an active research area of cognitive science. To overcome inaccessiblity of others' mental states, theoretical studies assume some mentalizing mechanism in the brain, including simulating others' behavior within knowledge of behavior of the self. We also present our computer-simulation study that tackles the role of mentalizing in a social environment, which examines behavior of agents based on reinforcement learning in Iterated Prisoners' Dilemma games. The results show that agents that choose actions using the estimated policy (corresponding to the mental state) of the co-player, achieve higher cooperation rates than control agents do, which choose actions using only the expected action of the co-player, or only the recent history of game plays.} }

@INPROCEEDINGS{Makino:2008e:Ox, author = {Makino, Takaki and Takagi, Toshihisa}, title = {On-line discovery of Temporal-Difference Networks}, booktitle = {ICML '08: Proceedings of the twenty-fifth international conference on machine learning}, year = 2008, publisher = {ACM Press}, address = {New York, NY, USA}, abstract = {We present an algorithm for on-line, incremental discovery of temporal-difference (TD) networks. The key contribution is the establishment of three criteria to expand a node in TD network: a node is expanded when the node is well-known, independent, and has a prediction error that requires further explanation. Since none of these criteria requires centralized calculation operations, they are easily computed in a parallel and distributed manner, and scalable for bigger problems compared to other discovery methods of predictive state representations. Through computer experiments, we demonstrate the empirical effectiveness of our algorithm.}, pdf = {Makino2008ICML.pdf} }

@ARTICLE{Takahashi:2008a:J, author = {Taiki Takahashi and Takaki Makino and Yu Ohmura and Hiroki Fukui}, title = {Employing delay and probability discounting frameworks for a neuroeconomic understanding of gambling behavior}, journal = {International Journal of Psychology Research}, year = {2008}, note = {To appear} }

@INPROCEEDINGS{Makino:2008f:P, author = {Takaki Makino and Taiki Takahashi and Hiroki Fukui}, title = {Modeling Decision Mechanism as a Reinforcement Learning with Probabilistic Discounting}, booktitle = {Proceedings of the 2nd WFSBP Asia-Pacific Congress}, year = {2008}, month = SEP, note = {To appear} }