scholarly journals The Pagoda Sequence: a Ramble through Linear Complexity, Number Walls, D0L Sequences, Finite State Automata, and Aperiodic Tilings

2009 ◽  
Vol 1 ◽  
pp. 130-148
Author(s):  
Fred Lunnon

Most interactions between users and augmented reality system (ARS) are that user assigns a marker to ARS, and the ARS responds the marker. In this context, a marker is mapped to an ARS's response, or in general, an array of markers is mapped to an array of ARS's responses. This interaction is a constant or linear complexity interaction since there is only a bijective mapping between a set of markers and a set of ARS's responses. In this research, we propose the expansion of user - ARS complexity into the polynomial. It is an interaction in which not only one marker for a single response (or an array of markers for an array of ARS's responses), but the interaction by which user provides a string of markers as a word of markers (i.e., a combination of multiple markers as a word) for a single ARS's response. The set of strings of markers to the ARS provided by users built a regular language. So that, the complexity of the user-ARS interaction became polynomial. This interaction was implemented by stating the user's language by means of a generalization of finite state automata (gFSA) and placing a universal Turing machine (UTM) between user and ARS, where the UTM as an interpreter translating or mapping the user language to ARS. To summarize our research, overall we apply the idea of a formal language into the interaction between the user and ARS, thereby changing the complexity of the interaction to polynomial even expandable to nondeterministic polynomials.


2015 ◽  
Vol 8 (3) ◽  
pp. 721-730 ◽  
Author(s):  
Shambhu Sharan ◽  
Arun K. Srivastava ◽  
S. P. Tiwari

2021 ◽  
Vol 178 (1-2) ◽  
pp. 59-76
Author(s):  
Emmanuel Filiot ◽  
Pierre-Alain Reynier

Copyless streaming string transducers (copyless SST) have been introduced by R. Alur and P. Černý in 2010 as a one-way deterministic automata model to define transductions of finite strings. Copyless SST extend deterministic finite state automata with a set of variables in which to store intermediate output strings, and those variables can be combined and updated all along the run, in a linear manner, i.e., no variable content can be copied on transitions. It is known that copyless SST capture exactly the class of MSO-definable string-to-string transductions, and are as expressive as deterministic two-way transducers. They enjoy good algorithmic properties. Most notably, they have decidable equivalence problem (in PSpace). On the other hand, HDT0L systems have been introduced for a while, the most prominent result being the decidability of the equivalence problem. In this paper, we propose a semantics of HDT0L systems in terms of transductions, and use it to study the class of deterministic copyful SST. Our contributions are as follows: (i)HDT0L systems and total deterministic copyful SST have the same expressive power, (ii)the equivalence problem for deterministic copyful SST and the equivalence problem for HDT0L systems are inter-reducible, in quadratic time. As a consequence, equivalence of deterministic SST is decidable, (iii)the functionality of non-deterministic copyful SST is decidable, (iv)determining whether a non-deterministic copyful SST can be transformed into an equivalent non-deterministic copyless SST is decidable in polynomial time.


2021 ◽  
Author(s):  
Giuseppe De Giacomo ◽  
Antonio Di Stasio ◽  
Giuseppe Perelli ◽  
Shufang Zhu

We study the impact of the need for the agent to obligatorily instruct the action stop in her strategies. More specifically we consider synthesis (i.e., planning) for LTLf goals under LTL environment specifications in the case the agent must mandatorily stop at a certain point. We show that this obligation makes it impossible to exploit the liveness part of the LTL environment specifications to achieve her goal, effectively reducing the environment specifications to their safety part only. This has a deep impact on the efficiency of solving the synthesis, which can sidestep handling Buchi determinization associated to LTL synthesis, in favor of finite-state automata manipulation as in LTLf synthesis. Next, we add to the agent goal, expressed in LTLf, a safety goal, expressed in LTL. Safety goals must hold forever, even when the agent stops, since the environment can still continue its evolution. Hence the agent, before stopping, must ensure that her safety goal will be maintained even after she stops. To do synthesis in this case, we devise an effective approach that mixes a synthesis technique based on finite-state automata (as in the case of LTLf goals) and model-checking of nondeterministic Buchi automata. In this way, again, we sidestep Buchi automata determinization, hence getting a synthesis technique that is intrinsically simpler than standard LTL synthesis.


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