# distributed optimization

- Compositionality
- composability
- Computer Theory and Trust
- access protocols
- Byzantine adversary detection
- computer science
- consensus iteration process
- Decision Making
- decision making problem
- decision theory
- distributed consensus algorithm
- distributed consensus problems
- distributed optimization
- economic engineering networked systems
- energy harvesting
- false trust
- graph theory
- Hardware
- Iterative methods
- Nonvolatile memory
- optimisation
- policy-based governance
- Policy-Governed Secure Collaboration
- Power supplies
- Program processors
- pubcrawl
- resilience
- Resiliency
- Scalability
- social engineering networked systems
- Task Analysis
- trust evaluation mechanism
- trust graph model
- trust propagation scheme
- trust-aware consensus algorithm

- adversarial
- adversarial nodes
- Big Data
- big data analysis methods
- Control Theory
- Control Theory and Privacy
- Cyber Physical System
- cyber physical systems
- cyber-physical systems
- data analysis
- data privacy
- different adversary models
- differential privacy
- Distributed databases
- distributed online learning algorithm
- distributed optimization
- graph theory
- Human behavior
- important data information
- learning (artificial intelligence)
- network topology
- online distributed optimization
- online learning
- optimization
- preliminary attempt
- privacy
- pubcrawl
- regular node
- resilience
- Resiliency
- Scalability
- sensitive data

## Towards Secure Large-Scale Networked Systems- Resilient Distributed Algorithms for Coordination in Networks under Cyber Attacks

Large-scale networked systems (such as the power grid, the internet, multi-robot systems, and smart cities) consist of a large number of interconnected components. To allow the entire system to function efficiently, these components must communicate with each other and use the exchanged information in order to estimate the state of the entire system and take optimal actions.

- 1-recall reinforcement learning
- agent dynamics
- automata theory
- continuous actions
- convergence
- Decision Making
- discrete actions
- distributed optimization
- game theory
- Games
- learning (artificial intelligence)
- learning automata
- Linear programming
- Markov processes
- multi-agent systems
- multiagent systems
- Nash equilibria
- Nash Equilibrium
- optimal equilibrium
- optimization
- payoff-based learning
- potential games
- pubcrawl170110
- stochastic approximation
- Stochastic processes
- strategic decision makers

## CPS: Breakthrough: Distributed Computing under Uncertainty: A New Paradigm for Cooperative Cyber-Physical Systems

### Abstract:

This project is to develop dynamical models of distributed computation systems that are resilient to noise, unreliable communication and other source uncertainty. The key idea is centered on the development of optimization systems. These are dynamical systems that (solve) stabilize around the optimal solution of a (static) convex optimization problem. If the optimization problem is separable, then the designed dynamic system decomposes into a set of locally interacting dynamic systems.

- constrained optimization
- constrained optimization problems
- continuous dynamic system
- continuous time systems
- Continuous-Time
- convergence
- Cost function
- distributed continuous-time optimization problem
- distributed optimization
- Eigenvalues and eigenfunctions
- equality constraints
- Equations
- global stability
- Heuristic algorithms
- information exchange
- Lagrangian Function
- Lagrangian functions
- Linear programming
- local convergence
- optimisation
- optimization
- stability
- Vectors