Actryx Ltd
Solutions for Complex Decision-Making and Intervention
We provide optimization solutions for intervention problems
such as those involving offline/static multi-stage and
online/dynamic (real-time) decision-making.
Practical problems are often too complexity to allow for an explicit
(i.e. logical) verification of the safety and optimality of the decision
rules; then approximate solutions, with verification through extensive simulation and
testing, has to be resorted to. By combining classical
logic (Logic AI), machine learning (Pattern AI) and modern simulation
technology (Process AI), Actryx's flexible modelling framework allows for
the rigorous modelling, simulation and testing of these problems.
Our solutions take into account
-
Dynamics - model dynamics causes time lags between intervention and
effects. In a decision/control context this results in feedback
mechanisms that must be accounted for;
-
Uncertainty - any source of uncertainty in models, observations and/or
measurements will require extensive simulation to generate the
statistical data for quantification of optimality, safety and risk (Monte-Carlo analysis) ;
-
Multi-objectivity - stakeholders have various perspectives which, at
best (e.g. when stakeholders collaborate), may be slightly variant with
each other; at worst (e.g. when stakeholders compete), objectives are
conflicting and the problem scope takes on a game setting;
-
Deadlines - hard real-time solutions require that deadlines be met. For
this reason Physical Time is a first-class concept in our models so
that deadlines can be tested for possible violation; if so it is an
indication that the model and/or computation scheme must be modified;
-
Explainability - our Process AI technology
produces traceable time-tagged events, underpinning the causality
structure that is essential to the explainability of our solutions.
Other solution features are
-
Modularization - approximate solutions result from breaking up an
infeasible problem into a hierarchy of feasible sub-problems and connecting the
sub-systems (i.e. modules) in a hierarchy of coordinated
interaction that guarantees the required levels of optimality, safety
and performance. Modularization also allows for a systematic capability
building that gradually includes more detail and complexity;
-
Robust - a modularized component structure and gradual capability
development process allows for a rigorous software testing policy resulting in
a reliable product;
-
Smooth development process - the same technolgy stack is used for rapid
iterative prototyping, proof-of-concept (PoC) development and product
commercialization. Thus, capitalizing on a continuity in acquiring
knowledge, this allows for a smooth transition from the feasiblity
(PoC) stage into the production stage.
Contact Us
Actryx Ltd (Reg 14254121)
20-22 Wenlock Road, N1 7GU, London, UK