This paper presents a semantics of self-adjusting computation and proves that the semantics are correct and consistent. The semantics integrate change propagation with the classic idea of memoization to enable reuse of computations under mutation to memory. During evaluation, reuse of a computation via memoization triggers a change propagation that adjusts the reused computation to reflect the ...

This paper presents an ASOCS (Adaptive Self-Organizing Concurrent System) model for massively parallel processing of incrementally defined rule systems in such areas as adaptive logic, robotics, logical inference, and dynamic control. An ASOCS is an adaptive network composed of many simple computing elements operating asynchronously and in parallel. This paper focuses on Adaptive Algorithm 2 (A...

Define a static algorithm to be an algorithm that computes some combinatorial property of its input consisting of static, i.e., non-moving, objects. In this paper, we describe a technique for syntactically transforming static algorithms into kinetic algorithms, which compute the statically computed property under motion, à la kinetic data structures. Based on the properties of the transformatio...

We present algorithms for a new self-adjusting binary search tree, which we call a shuffle tree. The tree is easy to implement and does not require parent pointers or balancing information to be stored in tree nodes. A maximum of one rotation is probabilistically applied during each traversal, which keeps the cost of balancing activity low. We present tests to compare the performance of shuffle...

Public transport driver scheduling is a world wide problem, which is NP-hard. Although some mathematically based methods are being used in the transport industry, there is still much scope for improvements. This paper presents a novel evolutionary approach that simulates the self-adjusting process on a single schedule. Five factors characterized by fuzzy membership functions are first aggregate...

In self-adjusting computation, programs respond automatically and efficiently to modifications to their data by tracking the dynamic data dependences of the computation and incrementally updating the output as needed. In this tutorial, we describe the self-adjustingcomputation model and present the language ∆ML (Delta ML) for writing self-adjusting programs.

We study the parametric controls of self-adjusting systems with numerical models. We investigate the situation where the target dynamics changes slowly and passes through a chaotic region. We find that feedback destabilizes controls if the target is chaotic. If the control is unstable the system migrates to the closest non-chaotic target, i.e. it adapts to the edge of chaos. For weak controls t...

Safety and comfort are primary concerns in rehabilitation devices and exoskeletons. However, the result of using simplified kinematic arrangements can be discomfort, or even injury, as a result of overconstraining the joint. In this paper, we describe a selfadjusting mechanism able to overcome misalignment between the rotational axis of the mechanism that is attached to the user’s limbs and the...

SplayNets are a distributed generalization of the classic splay tree data structures. Given a set of communication requests and a network comprised of n nodes, such that any pair of nodes is capable of establishing a direct connection, the goal is to dynamically find a (locally routable) binary tree topology, which connects all nodes and optimizes the routing cost for that communication pattern...

Proportional symbol maps are frequently used to represent numerical data. Commonly used symbols are squares or circles that are area-proportional to the numerical values. Proportional-symbol mapping is included in most geographic information systems (GIS) and is frequently used in digital atlases or Web mapping engines. Graduated symbols are simple for the map author to generate and easy for th...