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A Theory of Interactive Computation Jan van Leeuwen, Jiri Widermann Presented by Choi, Chang-Beom KAIST
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 2 Content Introduction A Model of Interactive Computation Interactively Computable Relations Interactive Recognitions Interactive Generations Interactive Translations Conclusion and Future works
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 3 Preliminary On-line Algorithm online algorithm is one that can process its input piece-by-piece, without having the entire input available from the start Example : Stock estimation Off-line Algorithm offline algorithm is given the whole problem data from the beginning and is required to output an answer which solves the problem Example : Summation of 1 ~ 100
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 4 Introduction Why “Interactive System”? Modern computer systems are built from components that communicate and compute, while interacting with their environment. Web Server & Client (Server/Client Model) Ubiquitous computing Traditional Model is incomplete! Why?
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 5 Purpose of Interactive System Not to compute some finial result React to environment or Interact with environment Maintain a well-defined action-reaction behavior
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 6 Why Traditional Model is Incomplete to Capture Interactive Properties Input is unpredictable Input is not specified in advance Interactive system never terminate (unless a fault occurs) Interactive system may change over time It is concurrent processes and continuing interaction
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 7 Examples of Inactive Systems Server Hacker Request Respond Attack Peer Server Sensor Inform Action Ubiquitous Environment Human Reaction
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 8 Difference Between Interactive System and Traditional System Traditional system There is no interaction between input and output Accepting input on initiation Producing output on termination Turing Machine with fixed input Interactive System Interaction between input and output Inputs can depend on intermediate outputs Traditional Turing Machine is not adequate to Interactive System
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 9 Content Introduction A Model of Interactive Computation Interactively Computable Relations Interactive Recognitions Interactive Generations Interactive Translations Conclusion and Future works
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 10 A Model of Interactive Computation Component (C) Environment (E) alphabet Alphabet Σ = {0, 1, τ, #}
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 11 Definitions C : Component E : Environment Alphabet : Σ = {0, 1, τ, #} 0, 1 : actual symbols τ : silent or empty symbol # : fault or error symbol Interactive input streams e = e 0 e 1 … e t … Interactive output streams c = c 0 c 1 … c t … (if C’s output is c then C is interactive component ) τ
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 12 Faults Fault Rules If C receives a symbol # from E, then C will output a # within a finite amount of time after this as well (and vice versa) If no #’s are exchanged, the interaction between E and C is called fault-free (error- free)
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 13 Definitions (Con’t) Assumptions E(C) sends a signal to C(E) during time t then C(E) “knows” this signal from next-time moments onward E is totally nondeterministic and unpredictable in generating its next signal E t-1 (c t-1 ) ∋ e t C’s output at time t is depend on e 0 e 1 …e t-1 and c 0 c 1 …c t-1 ē : e with out τ ċ : c with out τ τ
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 14 Interactiveness For all times t, when E sends a non-silent signal to C at time t, then C sends a non- silent signal to E at some time t’ with t’ > t and vice versa Non-silent silent t t+1 silent t+2 silent Non-silent t’ = t+3
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 15 Definition 1 An interaction pair of C and E is any pair (e,c) such that e = e 0 e 1 … e t … and c = c 0 c 1 … c t … represent an interactive computation of C in response to E Full environmental activity At all time t, E sends a non-silent signal to C Only for E, C can emit silent signal but for finite time
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 16 Component Memory space of C is always finite but potentially unbounded C can build up an infinite database of knowledge Algorithmicity Program evolves over time and which answers whether E t-1 (c t-1 ) ∋ e t or not Regardless of E’s actual behavior, there is an algorithmic way to verify afterwards that a sequence could have been generated by E
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 17 Interactive Transduction EC ec ω-transducer on infinite sequence
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 18 Definition 2 & 3 The behavior of C with respect to E is the set T C = {(e, ċ)|(e,c) is an interaction pair of C and E}. If (e,c) is an interaction pair of C and E, then we also write T C (e) = ċ and say that ċ is the interactive transduction of e by C A relation T on infinite sequences is called interactively computable iff there is an interactive component C such that T = T C
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 19 Example 0 * : set of finite sequences of 0’s (including empty sequence) 1 * : set of finite sequences of 1’s {0,1} * : set of all finite sequences over {0,1} {0,1} ω : set of infinite sequences or streams over {0,1}
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 20 Environment fools the Component There is no C can exist that transduces input streams of the from 1α1β1γ to output 1β1α1 with α, β ∈ 0 * and γ ∈ {0,1} ω Suppose C can transduce 1α1β1γ to 1β1α1 C must response to an input from E (100…) First symbol of c will be 1 If second symbol of c is 0 then E’s input will be 1α11γ If second symbol of c is 1 then E’s input will be 1α101γ If second symbol of c is # then it is not fault-free
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 21 Content Introduction A Model of Interactive Computation Interactively Computable Relations Interactive Recognitions Interactive Generations Interactive Translations Conclusion and Future works
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 22 Interactively Computable Relations Interactive computations can be view as classical, monotonic computations taken to infinity
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 23 Definition for Interactively Computable Relations y ∈ {0,1} ω and t ≥ 0 pref t (y) be length–t prefix of y x is a finite and strict prefix of y
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 24 Theorem 1 Proof Think about Turing Machine (M g ) which represents g with finite input stream x = pref t (u) M g simulates C Output of c is a signal 0 or 1 M g writes corresponding symbol Output of c is a silent symbol M g writes nothing Output of c is #, M g is sent to indefinite loop
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 25 Theorem 2 Proof => : Thm 1 <= Design a component C
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 26 Theorem 3 Interactiveness is recursively undecidable Proof Cantor’s Diagonal argument
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 27 Content Introduction A Model of Interactive Computation Interactively Computable Relations Interactive Recognitions Interactive Generations Interactive Translations Conclusion and Future works
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 28 Interactive Recognition Interactive systems perform tasks in monitoring Recognition of patterns in infinite streams of signals from environment (ex. intrusion detection system) Interactive system cannot detect that automaton (Component) passing an infinite number of times through one or more accepting states during the processing of the infinite input sequence In Interactive systems there is a specification which environment has to follow and component has to observe that this specification is adhere to.
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 29 Definitions
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 30 Lemma
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 31 Interactive Generations Proves that interactive generation and interactive recognition is dual Peer Server Sensor Inform Action Ubiquitous Environment Human Reaction
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 32 Interactive Translations Interactive components perform the online translation of infinite streams into other infinite streams of signal Related notion of omega-transduction Function f is interactively computable iff f is limit-continuous If f and g are interactively computable, then so is f °g Let f be interactively computable and 1-1. Then f -1 is interactively computable
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 33 Content Introduction A Model of Interactive Computation Interactively Computable Relations Interactive Recognitions Interactive Generations Interactive Translations Conclusion and Future works
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A Theory of Interactive Computation, presented by Choi, Chang-Beom, KAIST 34 Conclusion It requires knowledge of Basic Automata Theory Omega Language Theory Future works How about nonuniformly evolving of interactive systems and programs?
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