Hola,
¿eres nuevo aquí?

Regístrate gratis y conecta tu empresa con financiación pública, partners y proyectos.

Tengo cuenta

Regístrate

Ver video

MiLC

Financiado

Cerrado

Monotonicity in Logic and Complexity

MiLC will develop logical characterisations of monotone complexity classes, yielding languages and systems which are machine-independent and well suited for reasoning over such classes of functions. Monotone Boolean functions abou... ver más

31/08/2019

UCPH

200K€

Presupuesto del proyecto: 200K€

Líder del proyecto

KOBENHAVNS UNIVERSITET No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2019-08-31

MSCA-IF-2016: Individual Fellowships

I+D

Cerrada hace 8 años

0% 100%

Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

1 Participantes

UCPH

200.19K€ | Lider

Proyectos interesantes

LIPA

Software

Data Science

2M€ Cerrado

FINTOINF

Data Science

Applied Physics

197K€ Cerrado

ClaVa

Data Science

Software

161K€ Cerrado

LLAMA

Software

Data Science

176K€ Cerrado

MCC

Data Science

Software

2M€ Cerrado

NEAT

Software

Data Science

181K€ Cerrado

Conecta tu I+D

¿Tienes un proyecto y buscas un partner? Gracias a nuestro motor inteligente podemos recomendarte los mejores socios y ponerte en contacto con ellos. Te lo explicamos en este video

Duración del proyecto: 29 meses Fecha Inicio: 2017-03-17
Fecha Fin: 2019-08-31

Líder del proyecto

KOBENHAVNS UNIVERSITET No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 200K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto MiLC will develop logical characterisations of monotone complexity classes, yielding languages and systems which are machine-independent and well suited for reasoning over such classes of functions. Monotone Boolean functions abound in the theory of computation, e.g. in sorting algorithms and clique detection in graphs, and nonuniform classes of monotone functions have been well studied in computational complexity under the lens of monotone circuits. From the point of view of computation, monotone functions are computed by algorithms not using negation, and this will lead to several recursion-theoretic characterisations of feasible classes such as monotone P, NCi, ACi and the polynomial hierarchy. The main purpose of MiLC will be to capture these classes proof theoretically, by calibrating each class with the formally representable functions of a certain theory. MiLC will work in the setting of Bounded Arithmetic since its techniques are well suited to handling monotonicity, building on recently discovered correspondences with monotone proof complexity. To this end two avenues for controlling monotonicity will be investigated: (a) restricting negation in proofs, inducing monotone witnessing invariants, and (b) restricting structural rules of the underlying logic to eliminate the nonmonotone cases of witness extraction. The aim is to arrive at modular characterisations, where monotonicity of a represented class is switched on or off by the inclusion or exclusion, respectively, of certain structural rules. Finally MiLC will calibrate these theories with well studied systems in proof complexity, namely monotone, intuitionistic and deep inference systems, under the usual correspondence between theories of Bounded Arithmetic and systems of propositional logic. These tight correspondences ensure that the tools developed in MiLC may be employed to attack certain open problems in the area, reformulating and improving existing bounds.

Conecta tu I+D

Entra hoy

¿Olvidé mi contraseña?

Financiación

Empresas

CTIs/Universidades

Proyectos

Investigadores