334,037 research outputs found
Lower-bound Time-Complexity Analysis of Logic Programs
The paper proposes a technique for inferring conditions on goals that, when satisfied, ensure that a goal is sufficiently coarse-grained to warrant parallel evaluation. The method is powerful enough to reason about divide-and-conquer programs, and in the case of quicksort, for instance, can infer that a quicksort goal has a time complexity that exceeds 64 resolution steps (a threshold for spawning) if the input list is of length 10 or more. This gives a simple run-time tactic for controlling spawning. The method has been proved correct, can be implemented straightforwardly, has been demonstrated to be useful on a parallel machine, and, in contrast with much of the previous work on time-complexity analysis of logic programs, does not require any complicated difference equation solving machinery
Playing to Learn, or to Keep Secret: Alternating-Time Logic Meets Information Theory
Many important properties of multi-agent systems refer to the participants'
ability to achieve a given goal, or to prevent the system from an undesirable
event. Among intelligent agents, the goals are often of epistemic nature, i.e.,
concern the ability to obtain knowledge about an important fact \phi. Such
properties can be e.g. expressed in ATLK, that is, alternating-time temporal
logic ATL extended with epistemic operators. In many realistic scenarios,
however, players do not need to fully learn the truth value of \phi. They may
be almost as well off by gaining some knowledge; in other words, by reducing
their uncertainty about \phi. Similarly, in order to keep \phi secret, it is
often insufficient that the intruder never fully learns its truth value.
Instead, one needs to require that his uncertainty about \phi never drops below
a reasonable threshold.
With this motivation in mind, we introduce the logic ATLH, extending ATL with
quantitative modalities based on the Hartley measure of uncertainty. The new
logic enables to specify agents' abilities w.r.t. the uncertainty of a given
player about a given set of statements. It turns out that ATLH has the same
expressivity and model checking complexity as ATLK. However, the new logic is
exponentially more succinct than ATLK, which is the main technical result of
this paper
Programmable neural logic
Circuits of threshold elements (Boolean input, Boolean output neurons) have been shown to be surprisingly powerful. Useful functions such as XOR, ADD and MULTIPLY can be implemented by such circuits more efficiently than by traditional AND/OR circuits. In view of that, we have designed and built a programmable threshold element. The weights are stored on polysilicon floating gates, providing long-term retention without refresh. The weight value is increased using tunneling and decreased via hot electron injection. A weight is stored on a single transistor allowing the development of dense arrays of threshold elements. A 16-input programmable neuron was fabricated in the standard 2 Ī¼m double-poly, analog process available from MOSIS.
We also designed and fabricated the multiple threshold element introduced in [5]. It presents the advantage of reducing the area of the layout from O(n^2) to O(n); (n being the number of variables) for a broad class of Boolean functions, in particular symmetric Boolean functions such as PARITY.
A long term goal of this research is to incorporate programmable single/multiple threshold elements, as building blocks in field programmable gate arrays
A Component-oriented Framework for Autonomous Agents
The design of a complex system warrants a compositional methodology, i.e.,
composing simple components to obtain a larger system that exhibits their
collective behavior in a meaningful way. We propose an automaton-based paradigm
for compositional design of such systems where an action is accompanied by one
or more preferences. At run-time, these preferences provide a natural fallback
mechanism for the component, while at design-time they can be used to reason
about the behavior of the component in an uncertain physical world. Using
structures that tell us how to compose preferences and actions, we can compose
formal representations of individual components or agents to obtain a
representation of the composed system. We extend Linear Temporal Logic with two
unary connectives that reflect the compositional structure of the actions, and
show how it can be used to diagnose undesired behavior by tracing the
falsification of a specification back to one or more culpable components
Recommended from our members
MADX: Memristors-As-Drivers for Crossbar logic
Memristors have the potential to not only replace conventional memory, but also to open up new design possibilities because they store 1s and 0s as resistances rather than voltages. A memristor architecture that has attracted interest for its versatility and ease of integration with existing CMOS technologies is the crossbar array. In this paper, I modify the MAD scheme to create the MADX scheme for performing basic logic operations within a crossbar array. Then, I compare this scheme against two of the most well-known schemes, MAGIC and IMPLY. In the case study of a full-adder, both a one-bit and an 8-bit version, the MADX scheme achieves lower latency and substantially lower area requirements than both MAGIC and IMPLY. This is because it is more flexible about storing output values than either, does not destroy input values unlike IMPLY, and has more basic operations. In particular, it has XOR, which neither IMPLY nor MAGIC have and is useful for additionPlan II Honors Progra
Exposing Fake Logic
Exposing Fake Logic by Avi Sion is a collection of essays written after publication of his book A Fortiori Logic, in which he critically responds to derivative work by other authors who claim to know better. This is more than just polemics; but allows further clarifications of a fortiori logic and of general logic. This collection includes essays on: a fortiori argument (in general and in Judaism); Luis Duarte DāAlmeida; Mahmoud Zeraatpishe; Michael Avraham (et al.); an anonymous reviewer of BDD (a Bar Ilan University journal); and self-publishing
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