101 research outputs found
Unification and Logarithmic Space
We present an algebraic characterization of the complexity classes Logspace
and NLogspace, using an algebra with a composition law based on unification.
This new bridge between unification and complexity classes is inspired from
proof theory and more specifically linear logic and Geometry of Interaction.
We show how unification can be used to build a model of computation by means
of specific subalgebras associated to finite permutations groups. We then prove
that whether an observation (the algebraic counterpart of a program) accepts a
word can be decided within logarithmic space. We also show that the
construction can naturally represent pointer machines, an intuitive way of
understanding logarithmic space computing
Multi-Head Finite Automata: Characterizations, Concepts and Open Problems
Multi-head finite automata were introduced in (Rabin, 1964) and (Rosenberg,
1966). Since that time, a vast literature on computational and descriptional
complexity issues on multi-head finite automata documenting the importance of
these devices has been developed. Although multi-head finite automata are a
simple concept, their computational behavior can be already very complex and
leads to undecidable or even non-semi-decidable problems on these devices such
as, for example, emptiness, finiteness, universality, equivalence, etc. These
strong negative results trigger the study of subclasses and alternative
characterizations of multi-head finite automata for a better understanding of
the nature of non-recursive trade-offs and, thus, the borderline between
decidable and undecidable problems. In the present paper, we tour a fragment of
this literature
ViWiD: Leveraging WiFi for Robust and Resource-Efficient SLAM
Recent interest towards autonomous navigation and exploration robots for
indoor applications has spurred research into indoor Simultaneous Localization
and Mapping (SLAM) robot systems. While most of these SLAM systems use Visual
and LiDAR sensors in tandem with an odometry sensor, these odometry sensors
drift over time. To combat this drift, Visual SLAM systems deploy compute and
memory intensive search algorithms to detect `Loop Closures', which make the
trajectory estimate globally consistent. To circumvent these resource (compute
and memory) intensive algorithms, we present ViWiD, which integrates WiFi and
Visual sensors in a dual-layered system. This dual-layered approach separates
the tasks of local and global trajectory estimation making ViWiD resource
efficient while achieving on-par or better performance to state-of-the-art
Visual SLAM. We demonstrate ViWiD's performance on four datasets, covering over
1500 m of traversed path and show 4.3x and 4x reduction in compute and memory
consumption respectively compared to state-of-the-art Visual and Lidar SLAM
systems with on par SLAM performance
Finite state verifiers with constant randomness
We give a new characterization of as the class of languages
whose members have certificates that can be verified with small error in
polynomial time by finite state machines that use a constant number of random
bits, as opposed to its conventional description in terms of deterministic
logarithmic-space verifiers. It turns out that allowing two-way interaction
with the prover does not change the class of verifiable languages, and that no
polynomially bounded amount of randomness is useful for constant-memory
computers when used as language recognizers, or public-coin verifiers. A
corollary of our main result is that the class of outcome problems
corresponding to O(log n)-space bounded games of incomplete information where
the universal player is allowed a constant number of moves equals NL.Comment: 17 pages. An improved versio
Memoization for Unary Logic Programming: Characterizing PTIME
We give a characterization of deterministic polynomial time computation based
on an algebraic structure called the resolution semiring, whose elements can be
understood as logic programs or sets of rewriting rules over first-order terms.
More precisely, we study the restriction of this framework to terms (and logic
programs, rewriting rules) using only unary symbols. We prove it is complete
for polynomial time computation, using an encoding of pushdown automata. We
then introduce an algebraic counterpart of the memoization technique in order
to show its PTIME soundness. We finally relate our approach and complexity
results to complexity of logic programming. As an application of our
techniques, we show a PTIME-completeness result for a class of logic
programming queries which use only unary function symbols.Comment: Soumis {\`a} LICS 201
An Expressive Language and Efficient Execution System for Software Agents
Software agents can be used to automate many of the tedious, time-consuming
information processing tasks that humans currently have to complete manually.
However, to do so, agent plans must be capable of representing the myriad of
actions and control flows required to perform those tasks. In addition, since
these tasks can require integrating multiple sources of remote information ?
typically, a slow, I/O-bound process ? it is desirable to make execution as
efficient as possible. To address both of these needs, we present a flexible
software agent plan language and a highly parallel execution system that enable
the efficient execution of expressive agent plans. The plan language allows
complex tasks to be more easily expressed by providing a variety of operators
for flexibly processing the data as well as supporting subplans (for
modularity) and recursion (for indeterminate looping). The executor is based on
a streaming dataflow model of execution to maximize the amount of operator and
data parallelism possible at runtime. We have implemented both the language and
executor in a system called THESEUS. Our results from testing THESEUS show that
streaming dataflow execution can yield significant speedups over both
traditional serial (von Neumann) as well as non-streaming dataflow-style
execution that existing software and robot agent execution systems currently
support. In addition, we show how plans written in the language we present can
represent certain types of subtasks that cannot be accomplished using the
languages supported by network query engines. Finally, we demonstrate that the
increased expressivity of our plan language does not hamper performance;
specifically, we show how data can be integrated from multiple remote sources
just as efficiently using our architecture as is possible with a
state-of-the-art streaming-dataflow network query engine
Enhancements to the Timing Simulator of the Enhanced Modular Signal Processor
Computing and Information Science
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